Fairness Metrics Toolbox for Regression

(aiverify.stock.fairness-metrics-toolbox-for-regression) [source]

Description

This plugin computes and displays a list of fairness metrics to measure how correctly your regression model predicts among the given set of sensitive features.

Plugin Content

• Algorithms

Name	Description
Fairness Metrics Toolbox for Regression	The algorithm computes a list of fairness metrics to measure how correct your model predicts among the given set of sensitive features.

• Widgets

Name	Description
Introduction	To provide an introduction to the Fairness Metric Toolbox for Regression
Understanding Bar Chart	To guide your users on reading the generated bar chart
Bar Chart (MAE)	To generate the bar chart to show the mean absolute error parity between the subgroups
Bar Chart (MSE)	To generate the bar chart to show the mean square error parity between the subgroups
Bar Chart (R2)	To generate the bar chart to show the r2 score parity between the subgroups
Interpretation (MAE)	To interpret the mean absolute error parity results
Interpretation (MSE)	To interpret the mean square error parity results
Interpretation (R2)	To interpret the r2 score parity results
Recommendation	To provide a recommendation for fairness testing for regression models
Table of Definitions	To provide a table of definitions

Using the Plugin in AI Verify

Algorithm User Input(s)

Input Field	Description	Type
Sensitive Feature Name	Array of sensitive features names You may select multiple sensitive features of interest, and as a guide these are usually demographic features	array

Sample use of the widgets

More details

Algorithm input schema

{
    "title": "Algorithm Plugin Input Arguments",
    "description": "A schema for algorithm plugin input arguments",
    "type": "object",
    "required": [
        "sensitive_feature"
    ],
    "properties": {
        "sensitive_feature": {
            "title": "Sensitive Feature Names",
            "description": "Array of Sensitive Feature Names (e.g. Gender)",
            "type": "array",
            "items": {
                "type": "string"
            },
            "minItems": 1
        }
    }
}

Algorithm output schema

{
    "title": "Algorithm Plugin Output Arguments",
    "description": "A schema for algorithm plugin output arguments",
    "type": "object",
    "required": ["results"],
    "minProperties": 1,
    "properties": {
        "results": {
            "type": "array",
            "minItems": 1,
            "title": "The results Schema",
            "items": {
                "type": "object",
                "properties": {
                    "mae": {
                        "type": "number"
                    },
                    "r2": {
                        "type": [
                            "number",
                            "null"
                        ]
                    },
                    "mse": {
                        "type": "number"
                    },
                    "subgroup": {
                        "type": "string"
                    }
                }
            }
        }, 
        "sensitive_feature":{
            "description":"Array of sensitive feature names",
            "type":"array",
            "minItems":1,
            "items":{
                "type":"string"
            }
        }
    }
}