Module random_forest 

Random Forest implementation using SmartCore

This module provides Random Forest Classifier and Regressor implementations that create ensembles of Decision Trees with bootstrap sampling.

Structs

DiversityMeasures

Ensemble diversity measures for evaluating Random Forest and Extra Trees diversity

RandomForestClassifier

Random Forest Classifier

RandomForestConfig

Configuration for Random Forest

RandomForestRegressor

Random Forest Regressor

RegressionDiversityMeasures

Calculate diversity measures for regression ensembles

Enums

ClassWeight

Class balancing strategy for imbalanced datasets

SamplingStrategy

Sampling strategy for imbalanced datasets

Functions

balanced_bootstrap_sample

Generate balanced bootstrap sample indices

calculate_class_weights

Calculate class weights for balanced Random Forest

calculate_ensemble_diversity

Calculate comprehensive diversity measures for an ensemble of classifiers

calculate_regression_diversity

Calculate diversity measures for regression ensembles