Class RandomForestClassifier

Hierarchy

RandomForestBase
- RandomForestClassifier

Index

Constructors

Properties

estimators? indexes? n? oobResults?

Methods

getConfusionMatrix predict predictOOB predictProbability predictionValues selection toJSON train load

Constructors

constructor

new RandomForestClassifier(options: true | Partial<RandomForestBaseOptions>, model?: RandomForestClassifierModel): RandomForestClassifier
Create a new base random forest for a classifier or regression model.
Parameters
- options: true | Partial<RandomForestBaseOptions>
- Optional model: RandomForestClassifierModel
  
  for load purposes.
Returns RandomForestClassifier
Overrides RandomForestBase.constructor
- Defined in node_modules/ml-random-forest/types/types.d.ts:105

Properties

`Optional` estimators

estimators?: any[]

`Optional` indexes

indexes?: number[][]

`Optional` n

n?: number

`Optional` oobResults

oobResults?: {
    all: number[];
    predicted: number;
    true: number;
}[]

Out-Of-Bag results

Methods

getConfusionMatrix

getConfusionMatrix(): number[][]
Returns the confusion matrix Make sure to run train first.

Returns
- matrix.
Returns number[][]
- Defined in node_modules/ml-random-forest/types/types.d.ts:135

predict

predict(toPredict: number[][] | Matrix): number[]
Predicts the output given the matrix to predict.

Returns
predictions
Parameters
- toPredict: number[][] | Matrix
Returns number[]
Inherited from RandomForestBase.predict
- Defined in node_modules/ml-random-forest/types/types.d.ts:48

predictOOB

predictOOB(): number[]
Returns the Out-Of-Bag predictions.

Returns
predictions

Returns number[]
Inherited from RandomForestBase.predictOOB
- Defined in node_modules/ml-random-forest/types/types.d.ts:61

predictProbability

predictProbability(toPredict: number[][], label: number): number[]
Predicts the probability of a label given the matrix to predict.

Returns
predictions
Parameters
- toPredict: number[][]
- label: number
Returns number[]
- Defined in node_modules/ml-random-forest/types/types.d.ts:129

predictionValues

predictionValues(toPredict: number[][] | Matrix): Matrix
Predicts the output for every tree given the matrix to predict.

Returns
predictions
Parameters
- toPredict: number[][] | Matrix
Returns Matrix
Inherited from RandomForestBase.predictionValues
- Defined in node_modules/ml-random-forest/types/types.d.ts:68

selection

selection(values: any[]): number
retrieve the prediction given the selection method.

Returns
prediction
Parameters
- values: any[]
  
  predictions of the estimators.
Returns number
- Defined in node_modules/ml-random-forest/types/types.d.ts:111

toJSON

toJSON(): RandomForestClassifierModel
Export the current model to JSON.

Returns
- Current model.
Returns RandomForestClassifierModel
- Defined in node_modules/ml-random-forest/types/types.d.ts:116

train

train(trainingSet: number[][], trainingValues: number[]): void
Train the decision tree with the given training set and labels.
Parameters
- trainingSet: number[][]
- trainingValues: number[]
Returns void
Inherited from RandomForestBase.train
- Defined in node_modules/ml-random-forest/types/types.d.ts:54

`Static` load

load(model: RandomForestClassifierModel): RandomForestClassifier
Load a Decision tree classifier with the given model.

Returns
Parameters
- model: RandomForestClassifierModel
Returns RandomForestClassifier
- Defined in node_modules/ml-random-forest/types/types.d.ts:122

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