Class DecisionTreeRegression

Decision tree regression

Hierarchy

  • DecisionTree
    • DecisionTreeRegression

Constructors

constructor

Properties

_datas _depth _features _tree

Accessors

depth

Methods

_calcScore _calcValue fit importance init predict predict_value

Constructors

constructor

Properties

_datas

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

_depth

_depth: number

_features

_features: number

_tree

_tree: {
    children: any[];
    datas: { target: any; value: number[] }[];
    leafs: any;
    score: any;
    value: any;
}

Accessors

depth

  • 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

  • fit(): void

  • Fit model.

    Returns void

importance

  • importance(): number[]

  • Returns importances of the features.

    Returns number[]

    Importances

init

  • init(datas: number[][], targets: any[]): void

  • Initialize model.

    Parameters

    • datas: number[][]

      Training data

    • targets: any[]

      Target values

    Returns void

predict

  • predict(data: number[][]): number[]

  • Returns predicted values.

    Parameters

    • data: number[][]

      Sample data

    Returns number[]

    Predicted values

predict_value

  • predict_value(data: number[][]): number[]

  • Returns predicted values.

    Parameters

    • data: number[][]

      Sample data

    Returns number[]

    Predicted values

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