@ai-on-browser/data-analysis-models
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    Class DecisionTreeRegression

    Decision tree regression

    Hierarchy

    • DecisionTree
      • DecisionTreeRegression
    Index

    Constructors

    constructor

    Properties

    _datas _depth _features _tree

    Accessors

    depth

    Methods

    _calcScore _calcValue fit importance init predict predict_value

    Constructors

    Properties

    _datas

    _datas: { target: any; value: number[] }[] | undefined

    _depth

    _depth: number

    _features

    _features: number | undefined

    _tree

    _tree:
        | {
            children: never[];
            datas: { target: any; value: number[] }[];
            leafs: {
                children: never[];
                datas: { target: any; value: number[] }[];
                leafs: any[];
                score: any;
                value: any;
            }[];
            score: any;
            value: any;
        }
        | undefined

    Accessors

    • get depth(): number

      Depth of the tree

      Returns number

    Methods

    _calcScore

    • _calcScore(datas: any): number

      Parameters

      • datas: any

      Returns number

    _calcValue

    • _calcValue(datas: any): any

      Parameters

      • datas: any

      Returns any

    • Fit model.

      Returns void

    • Returns importances of the features.

      Returns number[]

      Importances

    • Initialize model.

      Parameters

      • datas: number[][]

        Training data

      • targets: any[]

        Target values

      Returns void

    • Returns predicted values.

      Parameters

      • data: number[][]

        Sample data

      Returns number[]

      Predicted values

    • Returns predicted values.

      Parameters

      • data: number[][]

        Sample data

      Returns number[]

      Predicted values

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