Class RandomForestRegressor

Random forest regressor

Hierarchy

RandomForest
- RandomForestRegressor

Index

Constructors

Properties

_samplingRate _trees

Accessors

Methods

_sample fit init predict predict_prob

Constructors

constructor

new RandomForestRegressor(
tree_num: number,
sampling_rate?: number,
): RandomForestRegressor
Parameters
- tree_num: number
  Number of trees
- Optionalsampling_rate: number
  Sampling rate
Returns RandomForestRegressor
Overrides RandomForest.constructor
- Defined in lib/model/random_forest.d.ts:26

Properties

_samplingRate

_samplingRate: number

_trees

_trees: any[]

Accessors

depth

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

Returns number
Inherited from RandomForest.depth
- Defined in lib/model/random_forest.d.ts:51

Methods

_sample

_sample(n: any): number[]
Parameters
- n: any
Returns number[]
Inherited from RandomForest._sample
- Defined in lib/model/random_forest.d.ts:52

fit

fit(): void
Fit model.

Returns void
Inherited from RandomForest.fit
- Defined in lib/model/random_forest.d.ts:62

init

init(datas: number[][], targets: any[]): void
Initialize model.
Parameters
- datas: number[][]
  Training data
- targets: any[]
  Target values
Returns void
Inherited from RandomForest.init
- Defined in lib/model/random_forest.d.ts:58

predict

predict(datas: number[][]): number[]
Returns predicted values.
Parameters
- datas: number[][]
  Sample data
Returns number[]
Predicted values
- Defined in lib/model/random_forest.d.ts:32

predict_prob

predict_prob(datas: number[][]): Map<number, number>[]
Returns probability of the datas.
Parameters
- datas: number[][]
  Sample data
Returns Map<number, number>[]
Predicted values
Inherited from RandomForest.predict_prob
- Defined in lib/model/random_forest.d.ts:68