Nondeterministic Programming Methodology

    shap-explainers
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    0.2.9 • Public • Published

    ShapExplainers

    This project contains the Angular components for the SHAP visual explainers:

    1. Shap Additive Force plot
    2. Shap Additive Force Array plot
    3. Custom: Shap Influence plot

    The project is based on the original code by https://github.com/slundberg/shap

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    Installation

    1. Run npm i shap-explainers
    2. Add ShapExplainersModule to the imports array
    3. Use the one of the following component selectors:
      • <shap-additive-force>
      • <shap-additive-force-array>
      • <shap-influence>

     

    API - How to use the components

    shap-additive-force component input parameters:

    Changing the colors of the plot. Requires an array of 2 colors.
    plotColors: string[] = ['rgb(222, 53, 13)', 'rgb(111, 207, 151)'];

    Changing the x-axis type between log-odds (identity) or probabilities (logit).
    link: 'logit' | 'identity' = 'identity';

    Setting the base value (middle point) for the plot:
    baseValue: number = 0.0;

    Set the label(s) for the output variables
    outNames: string[] = ['Color rating'];

    Hide the plot bars:
    hideBars: boolean = false;

    Set the margin for the labels (labels show up when hovering the bars when not enough space to display the labels)
    labelMargin: number = 0;

    Hide the label attached to the base value
    hideBaseValueLabel: boolean = false;

    The data with the feature names and feature values
    data: AdditiveForceData;

     

    shap-additive-force-array component input parameters:

    Set the offset from the top
    topOffset: number = 28;

    Set the offset from the left
    leftOffset: number = 80;

    Set the offset from the right
    rightOffset: number = 10;

    Set the height of the graph
    height: number = 350;

    Changing the colors of the plot. Requires an array of 2 colors.
    plotColors: string[] = ['rgb(222, 53, 13)', 'rgb(111, 207, 151)'];

    Changing the x-axis type between log-odds (identity) or probabilities (logit).
    link: 'logit' | 'identity' = 'identity';

    Setting the base value (middle point) for the plot:
    baseValue: number = 0.0;

    Set the label(s) for the output variables
    outNames: string[] = ['Color rating'];

    The data with the feature names and feature values
    data: AdditiveForceArrayData

     

    shap-influence component input parameters:

    Changing the colors of the signs (+/-). Requires an array of 2 colors.
    influenceColors: string[] = ['rgb(222, 53, 13)', 'rgb(111, 207, 151)'];

    Set the prediction values
    predictions: number[] = [1];

    Set the prediction label names
    predictionNames: string[] = ['Income']

    Set the amount of influence labels that are being displayed
    labelAmount: number = 7;

     

    Interfaces

    AdditiveForceData {
        featureNames: {
            [key: string]: string;
        };
        features: {
            [key: string]: { [key: string]: number };
        };
    }
    
    AdditiveForceArrayData {
        featureNames: {
            [key: string]: string;
        };
        explanations: {
            outValue: number;
            simIndex: number;
            features: {
                [key: string]: { value: number; effect: number; ind?: number };
            };
        }[];
    }
    
    InfluenceData {
        featureNames: {
            [key: string]: string;
        };
        valueNames: {
            [key: string]: string;
        };
        features: {
            [key: string]: { [key: string]: number };
        };
    }
    

     

    Repository

    Deeploy-ml/shap-explainers

    Install

    npm i shap-explainers

    Homepage

    deeploy.ml

    DownloadsWeekly Downloads

    94

    Version

    0.2.9

    License

    Apache-2.0

    Unpacked Size

    678 kB

    Total Files

    27

    Last publish

    Collaborators

    • deeploy
    • isanders
    • bwvdhelm