Disparate Impact Analysis (DIA) Explainer Demo

This example demonstrates how to interpret a scikit-learn model using the H2O Eval Studio library and retrieve the data and plot the Disparate Impact Analysis.

[1]:

import logging

import pandas
import webbrowser

from h2o_sonar import interpret
from h2o_sonar.lib.api import commons, explainers
from h2o_sonar.explainers.dia_explainer import DiaExplainer
from h2o_sonar.lib.api.models import ModelApi

from sklearn.ensemble import GradientBoostingClassifier

[2]:

results_location = "../../results"

# dataset
dataset_path = "../../data/creditcard.csv"
target_col = "default payment next month"
df = pandas.read_csv(dataset_path)
(X, y) = df.drop(target_col, axis=1), df[target_col]

[3]:

# parameters
interpret.describe_explainer(DiaExplainer)

[3]:

{'id': 'h2o_sonar.explainers.dia_explainer.DiaExplainer',
 'name': 'DiaExplainer',
 'display_name': 'Disparate Impact Analysis',
 'description': 'Disparate Impact Analysis (DIA) is a technique that is used to evaluate fairness. Bias can be introduced to models during the process of collecting, processing, and labeling data as a result, it is important to determine whether a model is harming certain users by making a significant number of biased decisions. DIA typically works by comparing aggregate measurements of unprivileged groups to a privileged group. For instance, the proportion of the unprivileged group that receives the potentially harmful outcome is divided by the proportion of the privileged group that receives the same outcome - the resulting proportion is then used to determine whether the model is biased.',
 'model_types': ['iid', 'time_series'],
 'can_explain': ['regression', 'binomial'],
 'explanation_scopes': ['global_scope'],
 'explanations': [{'explanation_type': 'global-disparate-impact-analysis',
   'name': 'DiaExplanation',
   'category': None,
   'scope': 'global',
   'has_local': None,
   'formats': []}],
 'parameters': [{'name': 'dia_cols',
   'description': 'List of features for which to compute DIA.',
   'comment': '',
   'type': 'list',
   'val': None,
   'predefined': [],
   'tags': [],
   'min_': 0.0,
   'max_': 0.0,
   'category': ''},
  {'name': 'cut_off',
   'description': 'Cut off.',
   'comment': '',
   'type': 'float',
   'val': 0.0,
   'predefined': [],
   'tags': [],
   'min_': 0.0,
   'max_': 0.0,
   'category': ''},
  {'name': 'maximize_metric',
   'description': 'Maximize metric.',
   'comment': '',
   'type': 'str',
   'val': 'F1',
   'predefined': ['F1', 'F05', 'F2', 'MCC'],
   'tags': [],
   'min_': 0.0,
   'max_': 0.0,
   'category': ''},
  {'name': 'max_cardinality',
   'description': 'Max cardinality for categorical variables.',
   'comment': '',
   'type': 'int',
   'val': 10,
   'predefined': [],
   'tags': [],
   'min_': 0.0,
   'max_': 0.0,
   'category': ''},
  {'name': 'min_cardinality',
   'description': 'Minimum cardinality for categorical variables.',
   'comment': '',
   'type': 'int',
   'val': 2,
   'predefined': [],
   'tags': [],
   'min_': 0.0,
   'max_': 0.0,
   'category': ''},
  {'name': 'num_card',
   'description': 'Max cardinality for numeric variables to be considered categorical.',
   'comment': '',
   'type': 'int',
   'val': 25,
   'predefined': [],
   'tags': [],
   'min_': 0.0,
   'max_': 0.0,
   'category': ''}],
 'keywords': ['run-by-default', 'explains-fairness', 'h2o-sonar']}

Interpret

[4]:

# scikit-learn model
gradient_booster = GradientBoostingClassifier(learning_rate=0.1)
gradient_booster.fit(X, y)

# explainable model
model = ModelApi().create_model(target_col=target_col, model_src=gradient_booster, used_features=X.columns.to_list())

interpretation = interpret.run_interpretation(
    dataset=df,
    model=model,
    target_col=target_col,
    results_location=results_location,
    log_level=logging.INFO,
    explainers=[
        commons.ExplainerToRun(
            explainer_id=DiaExplainer.explainer_id(),
            params="",
        )
    ]
)

/home/srasaratnam/projects/h2o-sonar/venv/lib/python3.8/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
  from .autonotebook import tqdm as notebook_tqdm
X does not have valid feature names, but GradientBoostingClassifier was fitted with feature names
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().

Preparing and checking DIA features (None): dataset=     | BILL_AMT5  LIMIT_BAL  default payment next month  PAY_5     ID  BILL_AMT6    AGE  BILL_AMT1  PAY_0  PAY_AMT2  …  BILL_AMT3  PAY_AMT5    SEX  PAY_6  PAY_2
     |     int64      int64                       int64  int64  int64      int64  int64      int64  int64     int64         int64     int64  int64  int64  int64
---- + ---------  ---------  --------------------------  -----  -----  ---------  -----  ---------  -----  --------     ---------  --------  -----  -----  -----
   0 |         0      20000                           1     -2      1          0     24       3913     -2       689  …        689         0      2     -2      2
   1 |      3455     120000                           1      0      2       3261     26       2682     -1      1000  …       2682         0      2      2      2
   2 |     14948      90000                           0      0      3      15549     34      29239      0      1500  …      13559      1000      2      0      0
   3 |     28959      50000                           0      0      4      29547     37      46990      1      2019  …      49291      1069      2      0      0
   4 |     19146      50000                           0      0      5      19131     57       8617      2     36681  …      35835       689      1      0      0
   5 |     19619      50000                           0      0      6      20024     37      64400      3      1815  …      57608      1000      1      0      0
   6 |    483003     500000                           0      0      7     473944     29     367965      4     40000  …     445007     13750      1      0      0
   7 |      -159     100000                           0      0      8        567     23      11876      5       601  …        601      1687      2     -1     -1
   8 |     11793     140000                           0      0      9       3719     28      11285      6         0  …      12108      1000      2      0      0
   9 |     13007      20000                           0     -1     10      13912     35          0      7         0  …          0      1122      1     -1     -2
  10 |      1828     200000                           0      0     11       3731     34      11073      8        12  …       5535      3738      2     -1      0
  11 |     22287     260000                           0     -1     12      13668     51      12261     -1      9966  …       9966         0      2      2     -1
  12 |      6500     630000                           0     -1     13       2870     41      12137     -1      6500  …       6500      2870      2     -1      0
  13 |     36137      70000                           1      0     14      36894     30      65802      1         0  …      65701      1500      1      2      2
  14 |     56875     250000                           0      0     15      55512     29      70887      0      3000  …      63561      3000      1      0      0
   … |         …          …                           …      …      …          …      …          …      …         …  …          …         …      …      …      …
9995 |         0     140000                           0     -2   9996          0     31          0      1         0  …          0         0      2     -2     -2
9996 |         0      80000                           0     -2   9997          0     37       3946     -2         0  …          0         0      2     -2     -2
9997 |    176717     200000                           0      0   9998     168431     44     138877      0      5000  …     142520     10017      1      0      0
9998 |         0      80000                           1     -2   9999          0     26        780     -1         0  …          0         0      2     -2      2
9999 |     19255     230000                           0      0  10000      17479     36      19505      0      3000  …      19750      3000      1      0      0
[10000 rows x 25 columns]
 dataset_meta={
  "shape": "(10000, 25)",
  "row_count": 10000,
  "column_names": [
    "ID",
    "LIMIT_BAL",
    "SEX",
    "EDUCATION",
    "MARRIAGE",
    "AGE",
    "PAY_0",
    "PAY_2",
    "PAY_3",
    "PAY_4",
    "PAY_5",
    "PAY_6",
    "BILL_AMT1",
    "BILL_AMT2",
    "BILL_AMT3",
    "BILL_AMT4",
    "BILL_AMT5",
    "BILL_AMT6",
    "PAY_AMT1",
    "PAY_AMT2",
    "PAY_AMT3",
    "PAY_AMT4",
    "PAY_AMT5",
    "PAY_AMT6",
    "default payment next month"
  ],
  "column_types": [
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int",
    "int"
  ],
  "column_uniques": [
    10000,
    72,
    2,
    7,
    4,
    54,
    11,
    11,
    11,
    11,
    10,
    10,
    8371,
    8215,
    8072,
    7913,
    7764,
    7550,
    3763,
    3581,
    3305,
    3247,
    3258,
    3174,
    2
  ],
  "columns_cat": [],
  "columns_num": [],
  "file_path": "",
  "file_name": "",
  "file_size": 0,
  "missing_values": [
    "",
    "?",
    "None",
    "nan",
    "NA",
    "N/A",
    "unknown",
    "inf",
    "-inf",
    "1.7976931348623157e+308",
    "-1.7976931348623157e+308"
  ],
  "columns_meta": [
    {
      "name": "ID",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": true,
      "is_numeric": true,
      "is_categorical": false,
      "count": 10000,
      "frequency": 0,
      "unique": 10000,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "LIMIT_BAL",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 72,
      "frequency": 0,
      "unique": 72,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "SEX",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 2,
      "frequency": 0,
      "unique": 2,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "EDUCATION",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 7,
      "frequency": 0,
      "unique": 7,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "MARRIAGE",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 4,
      "frequency": 0,
      "unique": 4,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "AGE",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 54,
      "frequency": 0,
      "unique": 54,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "PAY_0",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 11,
      "frequency": 0,
      "unique": 11,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "PAY_2",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 11,
      "frequency": 0,
      "unique": 11,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "PAY_3",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 11,
      "frequency": 0,
      "unique": 11,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "PAY_4",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 11,
      "frequency": 0,
      "unique": 11,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "PAY_5",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 10,
      "frequency": 0,
      "unique": 10,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "PAY_6",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 10,
      "frequency": 0,
      "unique": 10,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "BILL_AMT1",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 8371,
      "frequency": 0,
      "unique": 8371,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "BILL_AMT2",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 8215,
      "frequency": 0,
      "unique": 8215,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "BILL_AMT3",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 8072,
      "frequency": 0,
      "unique": 8072,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "BILL_AMT4",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 7913,
      "frequency": 0,
      "unique": 7913,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "BILL_AMT5",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 7764,
      "frequency": 0,
      "unique": 7764,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "BILL_AMT6",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 7550,
      "frequency": 0,
      "unique": 7550,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "PAY_AMT1",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 3763,
      "frequency": 0,
      "unique": 3763,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "PAY_AMT2",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 3581,
      "frequency": 0,
      "unique": 3581,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "PAY_AMT3",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 3305,
      "frequency": 0,
      "unique": 3305,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "PAY_AMT4",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 3247,
      "frequency": 0,
      "unique": 3247,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "PAY_AMT5",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 3258,
      "frequency": 0,
      "unique": 3258,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "PAY_AMT6",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 3174,
      "frequency": 0,
      "unique": 3174,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    },
    {
      "name": "default payment next month",
      "data_type": "int",
      "logical_types": [],
      "format": "",
      "is_id": false,
      "is_numeric": true,
      "is_categorical": false,
      "count": 2,
      "frequency": 0,
      "unique": 2,
      "max": null,
      "min": null,
      "mean": null,
      "std": null,
      "histogram_counts": [],
      "histogram_ticks": []
    }
  ]
}
Using dataset ENTITY to prepare DIA features: column_names=['ID', 'LIMIT_BAL', 'SEX', 'EDUCATION', 'MARRIAGE', 'AGE', 'PAY_0', 'PAY_2', 'PAY_3', 'PAY_4', 'PAY_5', 'PAY_6', 'BILL_AMT1', 'BILL_AMT2', 'BILL_AMT3', 'BILL_AMT4', 'BILL_AMT5', 'BILL_AMT6', 'PAY_AMT1', 'PAY_AMT2', 'PAY_AMT3', 'PAY_AMT4', 'PAY_AMT5', 'PAY_AMT6', 'default payment next month'] column_uniques=[10000, 72, 2, 7, 4, 54, 11, 11, 11, 11, 10, 10, 8371, 8215, 8072, 7913, 7764, 7550, 3763, 3581, 3305, 3247, 3258, 3174, 2]
DIA group columns prepared using dataset ENTITY: {'MARRIAGE', 'PAY_0', 'default payment next month', 'PAY_5', 'PAY_4', 'PAY_3', 'SEX', 'PAY_6', 'EDUCATION', 'PAY_2'}
DIA group columns to SKIP: {'model_pred', 'default payment next month'}
DIA group columns as BOOLs: [<h2o_sonar.methods.fairness._dia.BoolEntry object at 0x7f1d648c5880>, <h2o_sonar.methods.fairness._dia.BoolEntry object at 0x7f1d648c5940>, <h2o_sonar.methods.fairness._dia.BoolEntry object at 0x7f1d648c59a0>, <h2o_sonar.methods.fairness._dia.BoolEntry object at 0x7f1d648c5a00>, <h2o_sonar.methods.fairness._dia.BoolEntry object at 0x7f1d648c5a60>, <h2o_sonar.methods.fairness._dia.BoolEntry object at 0x7f1d648c5ac0>, <h2o_sonar.methods.fairness._dia.BoolEntry object at 0x7f1d648c5b20>, <h2o_sonar.methods.fairness._dia.BoolEntry object at 0x7f1d648c5b80>, <h2o_sonar.methods.fairness._dia.BoolEntry object at 0x7f1d648c5be0>]

A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().
A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().

../_images/notebooks_h2o-sonar-dia-explainer_5_3.png

../_images/notebooks_h2o-sonar-dia-explainer_5_4.png

../_images/notebooks_h2o-sonar-dia-explainer_5_5.png

../_images/notebooks_h2o-sonar-dia-explainer_5_6.png

../_images/notebooks_h2o-sonar-dia-explainer_5_7.png

../_images/notebooks_h2o-sonar-dia-explainer_5_8.png

../_images/notebooks_h2o-sonar-dia-explainer_5_9.png

../_images/notebooks_h2o-sonar-dia-explainer_5_10.png

../_images/notebooks_h2o-sonar-dia-explainer_5_11.png

../_images/notebooks_h2o-sonar-dia-explainer_5_12.png

../_images/notebooks_h2o-sonar-dia-explainer_5_13.png

../_images/notebooks_h2o-sonar-dia-explainer_5_14.png

../_images/notebooks_h2o-sonar-dia-explainer_5_15.png

../_images/notebooks_h2o-sonar-dia-explainer_5_16.png

../_images/notebooks_h2o-sonar-dia-explainer_5_17.png

../_images/notebooks_h2o-sonar-dia-explainer_5_18.png

../_images/notebooks_h2o-sonar-dia-explainer_5_19.png

../_images/notebooks_h2o-sonar-dia-explainer_5_20.png

../_images/notebooks_h2o-sonar-dia-explainer_5_21.png

../_images/notebooks_h2o-sonar-dia-explainer_5_22.png

../_images/notebooks_h2o-sonar-dia-explainer_5_23.png

../_images/notebooks_h2o-sonar-dia-explainer_5_24.png

../_images/notebooks_h2o-sonar-dia-explainer_5_25.png

../_images/notebooks_h2o-sonar-dia-explainer_5_26.png

../_images/notebooks_h2o-sonar-dia-explainer_5_27.png

../_images/notebooks_h2o-sonar-dia-explainer_5_28.png

../_images/notebooks_h2o-sonar-dia-explainer_5_29.png

../_images/notebooks_h2o-sonar-dia-explainer_5_30.png

../_images/notebooks_h2o-sonar-dia-explainer_5_31.png

../_images/notebooks_h2o-sonar-dia-explainer_5_32.png

../_images/notebooks_h2o-sonar-dia-explainer_5_33.png

../_images/notebooks_h2o-sonar-dia-explainer_5_34.png

../_images/notebooks_h2o-sonar-dia-explainer_5_35.png

../_images/notebooks_h2o-sonar-dia-explainer_5_36.png

../_images/notebooks_h2o-sonar-dia-explainer_5_37.png

../_images/notebooks_h2o-sonar-dia-explainer_5_38.png

../_images/notebooks_h2o-sonar-dia-explainer_5_39.png

../_images/notebooks_h2o-sonar-dia-explainer_5_40.png

../_images/notebooks_h2o-sonar-dia-explainer_5_41.png

../_images/notebooks_h2o-sonar-dia-explainer_5_42.png

../_images/notebooks_h2o-sonar-dia-explainer_5_43.png

../_images/notebooks_h2o-sonar-dia-explainer_5_44.png

../_images/notebooks_h2o-sonar-dia-explainer_5_45.png

../_images/notebooks_h2o-sonar-dia-explainer_5_46.png

../_images/notebooks_h2o-sonar-dia-explainer_5_47.png

../_images/notebooks_h2o-sonar-dia-explainer_5_48.png

../_images/notebooks_h2o-sonar-dia-explainer_5_49.png

../_images/notebooks_h2o-sonar-dia-explainer_5_50.png

../_images/notebooks_h2o-sonar-dia-explainer_5_51.png

../_images/notebooks_h2o-sonar-dia-explainer_5_52.png

../_images/notebooks_h2o-sonar-dia-explainer_5_53.png

../_images/notebooks_h2o-sonar-dia-explainer_5_54.png

../_images/notebooks_h2o-sonar-dia-explainer_5_55.png

../_images/notebooks_h2o-sonar-dia-explainer_5_56.png

../_images/notebooks_h2o-sonar-dia-explainer_5_57.png

../_images/notebooks_h2o-sonar-dia-explainer_5_58.png

../_images/notebooks_h2o-sonar-dia-explainer_5_59.png

../_images/notebooks_h2o-sonar-dia-explainer_5_60.png

../_images/notebooks_h2o-sonar-dia-explainer_5_61.png

../_images/notebooks_h2o-sonar-dia-explainer_5_62.png

../_images/notebooks_h2o-sonar-dia-explainer_5_63.png

../_images/notebooks_h2o-sonar-dia-explainer_5_64.png

../_images/notebooks_h2o-sonar-dia-explainer_5_65.png

../_images/notebooks_h2o-sonar-dia-explainer_5_66.png

../_images/notebooks_h2o-sonar-dia-explainer_5_67.png

../_images/notebooks_h2o-sonar-dia-explainer_5_68.png

../_images/notebooks_h2o-sonar-dia-explainer_5_69.png

../_images/notebooks_h2o-sonar-dia-explainer_5_70.png

../_images/notebooks_h2o-sonar-dia-explainer_5_71.png

../_images/notebooks_h2o-sonar-dia-explainer_5_72.png

../_images/notebooks_h2o-sonar-dia-explainer_5_73.png

../_images/notebooks_h2o-sonar-dia-explainer_5_74.png

../_images/notebooks_h2o-sonar-dia-explainer_5_75.png

../_images/notebooks_h2o-sonar-dia-explainer_5_76.png

../_images/notebooks_h2o-sonar-dia-explainer_5_77.png

../_images/notebooks_h2o-sonar-dia-explainer_5_78.png

../_images/notebooks_h2o-sonar-dia-explainer_5_79.png

../_images/notebooks_h2o-sonar-dia-explainer_5_80.png

../_images/notebooks_h2o-sonar-dia-explainer_5_81.png

../_images/notebooks_h2o-sonar-dia-explainer_5_82.png

../_images/notebooks_h2o-sonar-dia-explainer_5_83.png

../_images/notebooks_h2o-sonar-dia-explainer_5_84.png

../_images/notebooks_h2o-sonar-dia-explainer_5_85.png

../_images/notebooks_h2o-sonar-dia-explainer_5_86.png

../_images/notebooks_h2o-sonar-dia-explainer_5_87.png

../_images/notebooks_h2o-sonar-dia-explainer_5_88.png

../_images/notebooks_h2o-sonar-dia-explainer_5_89.png

../_images/notebooks_h2o-sonar-dia-explainer_5_90.png

../_images/notebooks_h2o-sonar-dia-explainer_5_91.png

../_images/notebooks_h2o-sonar-dia-explainer_5_92.png

../_images/notebooks_h2o-sonar-dia-explainer_5_93.png

../_images/notebooks_h2o-sonar-dia-explainer_5_94.png

../_images/notebooks_h2o-sonar-dia-explainer_5_95.png

../_images/notebooks_h2o-sonar-dia-explainer_5_96.png

../_images/notebooks_h2o-sonar-dia-explainer_5_97.png

../_images/notebooks_h2o-sonar-dia-explainer_5_98.png

../_images/notebooks_h2o-sonar-dia-explainer_5_99.png

../_images/notebooks_h2o-sonar-dia-explainer_5_100.png

../_images/notebooks_h2o-sonar-dia-explainer_5_101.png

Interact with the Explainer Result

[5]:

# retrieve the result
result = interpretation.get_explainer_result(DiaExplainer.explainer_id())

[6]:

# open interpretation HTML report in web browser
webbrowser.open(interpretation.result.get_html_report_location())

[6]:

True

[7]:

# summary
result.summary()

[7]:

{'id': 'h2o_sonar.explainers.dia_explainer.DiaExplainer',
 'name': 'DiaExplainer',
 'display_name': 'Disparate Impact Analysis',
 'description': 'Disparate Impact Analysis (DIA) is a technique that is used to evaluate fairness. Bias can be introduced to models during the process of collecting, processing, and labeling data as a result, it is important to determine whether a model is harming certain users by making a significant number of biased decisions. DIA typically works by comparing aggregate measurements of unprivileged groups to a privileged group. For instance, the proportion of the unprivileged group that receives the potentially harmful outcome is divided by the proportion of the privileged group that receives the same outcome - the resulting proportion is then used to determine whether the model is biased.',
 'model_types': ['iid', 'time_series'],
 'can_explain': ['regression', 'binomial'],
 'explanation_scopes': ['global_scope'],
 'explanations': [{'explanation_type': 'global-disparate-impact-analysis',
   'name': 'Disparate Impact Analysis',
   'category': 'DAI MODEL',
   'scope': 'global',
   'has_local': None,
   'formats': ['text/plain']},
  {'explanation_type': 'global-html-fragment',
   'name': 'Disparate Impact Analysis',
   'category': 'DAI MODEL',
   'scope': 'global',
   'has_local': None,
   'formats': ['text/html']}],
 'parameters': [{'name': 'dia_cols',
   'description': 'List of features for which to compute DIA.',
   'comment': '',
   'type': 'list',
   'val': None,
   'predefined': [],
   'tags': [],
   'min_': 0.0,
   'max_': 0.0,
   'category': ''},
  {'name': 'cut_off',
   'description': 'Cut off.',
   'comment': '',
   'type': 'float',
   'val': 0.0,
   'predefined': [],
   'tags': [],
   'min_': 0.0,
   'max_': 0.0,
   'category': ''},
  {'name': 'maximize_metric',
   'description': 'Maximize metric.',
   'comment': '',
   'type': 'str',
   'val': 'F1',
   'predefined': ['F1', 'F05', 'F2', 'MCC'],
   'tags': [],
   'min_': 0.0,
   'max_': 0.0,
   'category': ''},
  {'name': 'max_cardinality',
   'description': 'Max cardinality for categorical variables.',
   'comment': '',
   'type': 'int',
   'val': 10,
   'predefined': [],
   'tags': [],
   'min_': 0.0,
   'max_': 0.0,
   'category': ''},
  {'name': 'min_cardinality',
   'description': 'Minimum cardinality for categorical variables.',
   'comment': '',
   'type': 'int',
   'val': 2,
   'predefined': [],
   'tags': [],
   'min_': 0.0,
   'max_': 0.0,
   'category': ''},
  {'name': 'num_card',
   'description': 'Max cardinality for numeric variables to be considered categorical.',
   'comment': '',
   'type': 'int',
   'val': 25,
   'predefined': [],
   'tags': [],
   'min_': 0.0,
   'max_': 0.0,
   'category': ''}],
 'keywords': ['run-by-default', 'explains-fairness', 'h2o-sonar']}

[8]:

# parameters
result.params()

[8]:

{'dia_cols': ['MARRIAGE',
  'PAY_0',
  'PAY_5',
  'PAY_4',
  'PAY_3',
  'SEX',
  'PAY_6',
  'EDUCATION',
  'PAY_2'],
 'cut_off': 0.0,
 'maximize_metric': 'F1',
 'max_cardinality': 10,
 'min_cardinality': 2,
 'num_card': 25}

Display the DIA data

[9]:

# Print method help
import pprint
pprint.pprint(result.help())

{'methods': {'data': {'doc': '',
                      'parameters': [{'default': '',
                                      'doc': 'The name of the feature whose '
                                             'data we want to retrieve.',
                                      'name': 'feature_name',
                                      'required': True,
                                      'type': 'str'},
                                     {'default': '',
                                      'doc': 'The category of data to be '
                                             'retrieve. This can be one of the '
                                             "following: 'metrics', 'cm', "
                                             "'me_smd', 'disparity' and "
                                             "'parity'",
                                      'name': 'category',
                                      'required': True,
                                      'type': 'str'},
                                     {'default': 'The first reference level '
                                                 'will be selected from the '
                                                 'set of available reference '
                                                 'levels.',
                                      'doc': 'The reference levels for each '
                                             'categorical data',
                                      'name': 'ref_level',
                                      'required': False,
                                      'type': 'str | int'}]}}}

[10]:

result.data(feature_name="MARRIAGE", category=result.DiaCategory.DIA_METRICS)

[10]:

	Groups	N	Adverse Impact	Accuracy	True Positive Rate	Precision	Specificity	Negative Predicted Value	False Positive Rate	False Discovery Rate	False Negative Rate	False Omissions Rate
	▪▪▪▪▪▪▪▪	▪▪▪▪▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪
0	0	17	0.1314	0.7111	0.151394	0.260274	0.874435	0.7793	0.125565	0.739726	0.848606	0.2207
1	1	4390	0.136902	0.697722	0.155598	0.272879	0.869005	0.76511	0.130995	0.727121	0.844402	0.23489
2	2	5468	0.127835	0.72147	0.14966	0.251788	0.878145	0.790312	0.121855	0.748212	0.85034	0.209688
3	3	125	0.088	0.72	0.0714286	0.181818	0.907216	0.77193	0.0927835	0.818182	0.928571	0.22807

[11]:

result.data(feature_name="EDUCATION", category=result.DiaCategory.DIA_CATEGORY_DISPARITY, ref_level="3")

[11]:

	Groups	N	Adverse Impact Disparity	Marginal Error	Standardized Mean Difference	Accuracy Disparity	True Positive Rate Disparity	Precision Disparity	Specificity Disparity	Negative Predicted Value Disparity	False Positive Rate Disparity	False Discovery Rate Disparity	False Negative Rate Disparity	False Omissions Rate Disparity
	▪▪▪▪▪▪▪▪	▪▪▪▪▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪▪▪▪▪	▪▪▪▪	▪▪▪▪▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪▪▪▪▪	▪▪▪▪
0	0	3	1.14795	−0.0169346	0.647818	1.01586	1.19602	0.947397	0.983019	1.03222	1.13675	1.01993	0.971592	0.900712
1	1	3714	1.4137	−0.0473547	0.140163	1.02392	1.65135	0.981165	0.956258	1.06373	1.35226	1.00713	0.905601	0.803646
2	2	4588	0.971119	0.00330586	−0.00978488	1.01227	0.933703	0.913569	1.00166	1.01436	0.986664	1.03274	1.00961	0.95574
3	3	1590	1	0	0	1	1	1	1	1	1	1	1	1
4	4	26	1.34404	−0.0393808	0.116561	1.15385	0	0	0.944309	1.26435	1.44848	1.37879	1.14493	0.185507
5	5	69	1.51935	−0.0594476	0.175956	1.15942	3.16	0.606667	0.948524	1.25484	1.41454	1.14899	0.686957	0.214798
6	6	10	3.49451	−0.285535	0.845141	0.857143	NA	0	0.674506	1.32455	3.62121	1.37879	NA	0

[12]:

result.data(feature_name="PAY_4", category=result.DiaCategory.DIA_CATEGORY_CM, ref_level=-1)

[12]:

	actual1	actual0
	▪▪▪▪	▪▪▪▪
0	49	208
1	287	1436

[13]:

result.data(feature_name="SEX", category=result.DiaCategory.DIA_CATEGORY_ME_SMD)

[13]:

	Groups	N	Marginal Error	Standardized Mean Difference
	▪▪▪▪▪▪▪▪	▪▪▪▪▪▪▪▪	▪▪▪▪	▪▪▪▪▪▪▪▪
0	1	4206	0	0
1	2	5794	−0.0101226	0.0299615

[14]:

result.data(feature_name="PAY_2", category=result.DiaCategory.DIA_CATEGORY_PARITY)

[14]:

	Groups	N	Adverse Impact Parity	Accuracy Parity	True Positive Rate Parity	Precision Parity	Specificity Parity	Negative Predicted Value Parity	False Positive Rate Parity	False Discovery Rate Parity	…	Type I Parity	Type II Parity	Equalized Odds	Supervised Fairness	Overall Fairness
	▪▪▪▪	▪▪▪▪▪▪▪▪	▪	▪	▪	▪	▪	▪	▪	▪		▪	▪	▪	▪	▪
0	-2	1218	1	1	1	1	1	1	1	1	…	1	1	1	1	1
1	-1	2171	0	1	0	0	0	1	0	1	…	0	0	0	0	0
2	0	5147	0	1	0	1	0	1	0	1	…	0	0	0	0	0
3	1	8	0	1	0	0	0	1	0	0	…	0	0	0	0	0
4	2	1294	0	0	0	0	0	0	0	0	…	0	0	0	0	0
5	3	106	0	0	0	0	0	0	0	0	…	0	0	0	0	0
6	4	25	0	1	0	0	0	0	0	0	…	0	0	0	0	0
7	5	11	0	0	0	0	0	0	0	0	…	0	0	0	0	0
8	6	7	0	0	0	0	0	0	0	0	…	0	0	0	0	0
9	7	12	0	1	0	0	0	0	0	0	…	0	0	0	0	0
10	8	1	0	0	0	0	0	1	0	0	…	0	0	0	0	0
11	all	10000	0	0	0	0	0	0	0	0	…	0	0	0	0	0

[15]:

result.data(feature_name="MARRIAGE", category=result.DiaCategory.DIA_CATEGORY_DISPARITY)

[15]:

	Groups	N	Adverse Impact Disparity	Marginal Error	Standardized Mean Difference	Accuracy Disparity	True Positive Rate Disparity	Precision Disparity	Specificity Disparity	Negative Predicted Value Disparity	False Positive Rate Disparity	False Discovery Rate Disparity	False Negative Rate Disparity	False Omissions Rate Disparity
	▪▪▪▪▪▪▪▪	▪▪▪▪▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪	▪▪▪▪
0	0	17	1	0	0	1	1	1	1	1	1	1	1	1
1	1	4390	1.04187	−0.00550205	−0.117117	0.981187	1.02776	1.04843	0.99379	0.981791	1.04324	0.982961	0.995047	1.0643
2	2	5468	0.972867	0.00356533	−0.143955	1.01458	0.988543	0.967397	1.00424	1.01413	0.970449	1.01147	1.00204	0.950102
3	3	125	0.669711	0.0434	−0.26186	1.01252	0.471805	0.698565	1.03749	0.990542	0.738927	1.10606	1.09423	1.03339

Plot the DIA Metrics

[16]:

result.plot(feature_name="EDUCATION")

../_images/notebooks_h2o-sonar-dia-explainer_20_0.png

../_images/notebooks_h2o-sonar-dia-explainer_20_1.png

../_images/notebooks_h2o-sonar-dia-explainer_20_2.png

../_images/notebooks_h2o-sonar-dia-explainer_20_3.png

../_images/notebooks_h2o-sonar-dia-explainer_20_4.png

../_images/notebooks_h2o-sonar-dia-explainer_20_5.png

../_images/notebooks_h2o-sonar-dia-explainer_20_6.png

../_images/notebooks_h2o-sonar-dia-explainer_20_7.png

../_images/notebooks_h2o-sonar-dia-explainer_20_8.png

../_images/notebooks_h2o-sonar-dia-explainer_20_9.png

../_images/notebooks_h2o-sonar-dia-explainer_20_10.png

[16]:

[]

[17]:

# Only plot metric for "Specificity"
result.plot(feature_name="PAY_0", metrics_of_interest="Specificity")

../_images/notebooks_h2o-sonar-dia-explainer_21_0.png

[17]:

[]

[18]:

# Only plot metrics for "N", "Adverse Impact" and "True Positive Rate"
result.plot(feature_name="PAY_0", metrics_of_interest=["N", "Adverse Impact", "True Positive Rate"])

../_images/notebooks_h2o-sonar-dia-explainer_22_0.png

../_images/notebooks_h2o-sonar-dia-explainer_22_1.png

../_images/notebooks_h2o-sonar-dia-explainer_22_2.png

[18]:

[]

Save the explainer log and data

[19]:

# save the explainer log
result.log(path="./dia-demo.log")

[20]:

!head dia-demo.log

[21]:

# save the explainer data
result.zip(file_path="./dia-demo-archive.zip")

[22]:

!unzip -l dia-demo-archive.zip

Archive:  dia-demo-archive.zip
  Length      Date    Time    Name
---------  ---------- -----   ----
     3890  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/result_descriptor.json
      117  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_disparate_impact_analysis/text_plain.meta
       19  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_disparate_impact_analysis/text_plain/explanation.txt
     4078  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/dia_entity.json
     2248  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/metrics.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/7/cm.jay
     2768  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/7/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/7/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/7/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/8/cm.jay
     2768  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/8/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/8/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/8/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/9/cm.jay
     2768  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/9/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/9/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/9/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/2/cm.jay
     2760  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/2/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/2/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/2/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/5/cm.jay
     2768  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/5/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/5/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/5/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/10/cm.jay
     2784  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/10/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/10/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/10/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/1/cm.jay
     2760  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/1/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/1/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/1/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/3/cm.jay
     2776  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/3/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/3/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/3/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/6/cm.jay
     2768  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/6/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/6/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/6/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/0/cm.jay
     2760  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/0/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/0/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/0/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/4/cm.jay
     2760  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/4/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/4/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_3/4/parity.jay
     1504  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/metrics.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/2/cm.jay
     1928  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/2/disparity.jay
      656  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/2/me_smd.jay
     2008  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/2/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/1/cm.jay
     1928  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/1/disparity.jay
      656  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/1/me_smd.jay
     2008  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/1/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/3/cm.jay
     1928  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/3/disparity.jay
      656  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/3/me_smd.jay
     2008  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/3/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/0/cm.jay
     1928  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/0/disparity.jay
      656  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/0/me_smd.jay
     2008  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/MARRIAGE/0/parity.jay
     2152  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/metrics.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/7/cm.jay
     2680  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/7/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/7/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/7/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/8/cm.jay
     2680  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/8/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/8/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/8/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/9/cm.jay
     2680  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/9/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/9/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/9/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/2/cm.jay
     2664  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/2/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/2/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/2/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/5/cm.jay
     2680  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/5/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/5/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/5/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/10/cm.jay
     2680  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/10/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/10/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/10/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/1/cm.jay
     2664  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/1/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/1/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/1/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/3/cm.jay
     2688  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/3/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/3/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/3/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/6/cm.jay
     2680  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/6/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/6/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/6/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/0/cm.jay
     2664  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/0/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/0/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/0/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/4/cm.jay
     2664  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/4/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/4/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_4/4/parity.jay
     2056  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/metrics.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/7/cm.jay
     2568  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/7/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/7/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/7/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/8/cm.jay
     2568  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/8/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/8/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/8/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/9/cm.jay
     2584  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/9/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/9/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/9/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/2/cm.jay
     2552  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/2/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/2/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/2/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/5/cm.jay
     2568  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/5/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/5/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/5/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/1/cm.jay
     2552  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/1/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/1/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/1/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/3/cm.jay
     2568  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/3/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/3/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/3/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/6/cm.jay
     2568  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/6/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/6/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/6/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/0/cm.jay
     2552  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/0/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/0/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/0/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/4/cm.jay
     2568  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/4/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/4/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_6/4/parity.jay
     2056  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/metrics.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/7/cm.jay
     2576  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/7/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/7/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/7/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/8/cm.jay
     2592  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/8/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/8/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/8/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/9/cm.jay
     2592  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/9/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/9/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/9/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/2/cm.jay
     2568  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/2/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/2/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/2/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/5/cm.jay
     2568  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/5/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/5/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/5/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/10/cm.jay
     2592  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/10/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/10/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/10/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/1/cm.jay
     2568  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/1/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/1/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/1/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/3/cm.jay
     2568  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/3/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/3/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/3/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/6/cm.jay
     2576  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/6/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/6/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/6/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/0/cm.jay
     2568  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/0/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/0/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/0/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/4/cm.jay
     2568  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/4/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/4/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_0/4/parity.jay
     2248  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/metrics.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/7/cm.jay
     2768  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/7/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/7/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/7/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/8/cm.jay
     2784  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/8/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/8/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/8/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/9/cm.jay
     2768  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/9/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/9/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/9/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/2/cm.jay
     2760  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/2/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/2/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/2/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/5/cm.jay
     2760  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/5/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/5/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/5/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/10/cm.jay
     2776  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/10/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/10/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/10/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/1/cm.jay
     2760  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/1/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/1/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/1/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/3/cm.jay
     2768  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/3/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/3/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/3/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/6/cm.jay
     2768  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/6/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/6/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/6/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/0/cm.jay
     2760  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/0/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/0/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/0/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/4/cm.jay
     2760  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/4/disparity.jay
      856  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/4/me_smd.jay
     2224  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_2/4/parity.jay
     1800  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/metrics.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/2/cm.jay
     2264  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/2/disparity.jay
      744  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/2/me_smd.jay
     2056  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/2/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/5/cm.jay
     2264  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/5/disparity.jay
      744  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/5/me_smd.jay
     2056  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/5/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/1/cm.jay
     2264  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/1/disparity.jay
      744  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/1/me_smd.jay
     2056  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/1/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/3/cm.jay
     2264  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/3/disparity.jay
      744  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/3/me_smd.jay
     2056  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/3/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/6/cm.jay
     2280  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/6/disparity.jay
      744  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/6/me_smd.jay
     2056  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/6/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/0/cm.jay
     2264  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/0/disparity.jay
      744  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/0/me_smd.jay
     2056  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/0/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/4/cm.jay
     2272  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/4/disparity.jay
      744  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/4/me_smd.jay
     2056  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/EDUCATION/4/parity.jay
     2152  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/metrics.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/7/cm.jay
     2664  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/7/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/7/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/7/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/8/cm.jay
     2656  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/8/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/8/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/8/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/9/cm.jay
     2672  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/9/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/9/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/9/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/2/cm.jay
     2648  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/2/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/2/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/2/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/5/cm.jay
     2656  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/5/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/5/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/5/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/1/cm.jay
     2648  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/1/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/1/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/1/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/3/cm.jay
     2648  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/3/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/3/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/3/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/6/cm.jay
     2656  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/6/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/6/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/6/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/0/cm.jay
     2648  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/0/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/0/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/0/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/4/cm.jay
     2656  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/4/disparity.jay
      824  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/4/me_smd.jay
     2208  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/PAY_5/4/parity.jay
     1392  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/SEX/metrics.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/SEX/1/cm.jay
     1792  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/SEX/1/disparity.jay
      600  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/SEX/1/me_smd.jay
     1984  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/SEX/1/parity.jay
      304  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/SEX/0/cm.jay
     1792  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/SEX/0/disparity.jay
      600  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/SEX/0/me_smd.jay
     1984  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/work/SEX/0/parity.jay
      110  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html.meta
    15867  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-8-true_positive_rate.png
    13555  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-7-n.png
    16989  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-1-false_omissions_rate.png
    14767  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-8-precision.png
    15218  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-8-false_omissions_rate.png
    16450  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-0-false_discovery_rate.png
    15255  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-6-false_omissions_rate.png
    14397  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-2-n.png
    14336  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-3-n.png
    14870  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-1-true_positive_rate.png
    14883  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-5-adverse_impact.png
    14398  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-2-true_positive_rate.png
    14627  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-4-adverse_impact.png
    15710  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-5-true_positive_rate.png
    16873  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-3-false_discovery_rate.png
    15736  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-3-negative_predicted_value.png
    15279  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-8-false_discovery_rate.png
    15751  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-2-adverse_impact.png
    13643  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-3-precision.png
    16982  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-2-false_discovery_rate.png
    13261  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-5-false_omissions_rate.png
    15192  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-2-false_negative_rate.png
    14237  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-6-specificity.png
    14495  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-6-true_positive_rate.png
    14368  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-5-false_discovery_rate.png
    15098  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-7-false_negative_rate.png
    15176  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-2-false_omissions_rate.png
    11702  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-5-specificity.png
    12554  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-5-precision.png
    15055  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-1-accuracy.png
    13924  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-0-n.png
    18183  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-8-false_positive_rate.png
    14259  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-1-specificity.png
    14691  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-6-precision.png
    15847  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-4-true_positive_rate.png
    14741  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-5-false_positive_rate.png
    15134  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-3-adverse_impact.png
    15076  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-4-false_negative_rate.png
    13932  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-4-accuracy.png
    16250  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-3-false_omissions_rate.png
    13838  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-1-precision.png
    17735  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-7-adverse_impact.png
    16853  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-1-false_positive_rate.png
    15310  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-1-false_discovery_rate.png
    14982  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-0-false_omissions_rate.png
    17054  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-6-false_discovery_rate.png
    15347  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-6-false_negative_rate.png
    14406  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-8-n.png
    16217  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-6-false_positive_rate.png
    29111  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/explanation.html
    13388  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-0-specificity.png
    13915  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-3-accuracy.png
    16176  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-7-false_omissions_rate.png
    14158  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-2-specificity.png
    15004  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-3-false_positive_rate.png
    14172  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-4-specificity.png
    14109  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-3-specificity.png
    15577  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-7-accuracy.png
    18141  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-7-false_positive_rate.png
    15202  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-4-false_omissions_rate.png
    12924  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-5-accuracy.png
    15074  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-3-false_negative_rate.png
    13915  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-8-accuracy.png
    14411  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-1-n.png
    15635  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-2-false_positive_rate.png
    16429  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-1-adverse_impact.png
    15531  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-1-negative_predicted_value.png
    14226  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-0-precision.png
    15597  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-5-negative_predicted_value.png
    14298  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-0-false_negative_rate.png
    15906  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-8-negative_predicted_value.png
    15790  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-4-negative_predicted_value.png
    17393  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-0-true_positive_rate.png
    16560  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-0-adverse_impact.png
    14589  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-0-accuracy.png
    13899  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-2-accuracy.png
    13229  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-5-n.png
    15029  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-5-false_negative_rate.png
    14717  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-7-precision.png
    15757  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-2-negative_predicted_value.png
    16915  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-4-false_discovery_rate.png
    15606  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-6-accuracy.png
    16424  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-3-true_positive_rate.png
    14433  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-6-n.png
    15739  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-7-negative_predicted_value.png
    15492  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-6-negative_predicted_value.png
    13765  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-7-specificity.png
    15021  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-4-false_positive_rate.png
    13748  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-2-precision.png
    14108  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-8-adverse_impact.png
    15098  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-8-false_negative_rate.png
    16390  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-0-false_positive_rate.png
    17928  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-7-true_positive_rate.png
    15177  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-1-false_negative_rate.png
    13677  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-4-precision.png
    17088  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-0-negative_predicted_value.png
    14172  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-8-specificity.png
    15296  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-7-false_discovery_rate.png
    15822  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-6-adverse_impact.png
    14403  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/global_html_fragment/text_html/dia-4-n.png
        2  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/model_problems/problems_and_actions.json
        0  2023-03-12 23:07   explainer_h2o_sonar_explainers_dia_explainer_DiaExplainer_1d88b336-a4d5-4d1a-8e2d-492d577e4096/log/explainer_run_1d88b336-a4d5-4d1a-8e2d-492d577e4096.log
---------                     -------
  2005483                     424 files

[ ]: