Class ExtraTreesRegressor

Extra trees regressor

Hierarchy

ExtraTrees
- ExtraTreesRegressor

Index

Constructors

Properties

_depth _samplingRate _trees

Accessors

Methods

_predict_leafs _sample fit init predict

Constructors

constructor

new ExtraTreesRegressor(
tree_num: number,
sampling_rate?: number,
): ExtraTreesRegressor
Parameters
- tree_num: number
  Number of trees
- Optionalsampling_rate: number
  Sampling rate
Returns ExtraTreesRegressor
Inherited from ExtraTrees.constructor
- Defined in lib/model/extra_trees.d.ts:31

Properties

_depth

_depth: number

_samplingRate

_samplingRate: number

_trees

_trees: { children: any[]; data: any; target: any }[]

Accessors

depth

get depth(): number
The max depth among the trees.

Returns number
Inherited from ExtraTrees.depth
- Defined in lib/model/extra_trees.d.ts:43

Methods

_predict_leafs

_predict_leafs(datas: any): any
Parameters
- datas: any
Returns any
Inherited from ExtraTrees._predict_leafs
- Defined in lib/model/extra_trees.d.ts:55

_sample

_sample(n: any): number[]
Parameters
- n: any
Returns number[]
Inherited from ExtraTrees._sample
- Defined in lib/model/extra_trees.d.ts:44

fit

fit(): void
Fit model.

Returns void
Inherited from ExtraTrees.fit
- Defined in lib/model/extra_trees.d.ts:54

init

init(datas: number[][], targets: any[]): void
Initialize model.
Parameters
- datas: number[][]
  Training data
- targets: any[]
  Target values
Returns void
Inherited from ExtraTrees.init
- Defined in lib/model/extra_trees.d.ts:50

predict

predict(datas: number[][]): number[]
Returns predicted values.
Parameters
- datas: number[][]
  Sample data
Returns number[]
Predicted values
- Defined in lib/model/extra_trees.d.ts:21