RandomForestRegressor Class Reference

Implements a Random Forest Regressor. More...

#include <RandomForestRegressor.hpp>

Public Member Functions
	RandomForestRegressor (int n_estimators=10, int max_depth=5, int min_samples_split=2, int max_features=-1)
	Constructs a RandomForestRegressor. More...
	~RandomForestRegressor ()=default
	Destructor for RandomForestRegressor.
void	fit (const std::vector< std::vector< double >> &X, const std::vector< double > &y)
	Fits the model to the training data. More...
std::vector< double >	predict (const std::vector< std::vector< double >> &X) const
	Predicts target values for given input data. More...

Detailed Description

Implements a Random Forest Regressor.

Constructor & Destructor Documentation

RandomForestRegressor()

RandomForestRegressor::RandomForestRegressor	(	int	n_estimators = 10,
		int	max_depth = 5,
		int	min_samples_split = 2,
		int	max_features = -1
	)

Constructs a RandomForestRegressor.

Parameters

n_estimators	The number of trees in the forest.
max_depth	The maximum depth of the tree.
min_samples_split	The minimum number of samples required to split an internal node.
max_features	The number of features to consider when looking for the best split. Defaults to sqrt(num_features).

Member Function Documentation

fit()

void RandomForestRegressor::fit	(	const std::vector< std::vector< double >> &	X,
		const std::vector< double > &	y
	)

Fits the model to the training data.

Parameters

X	A vector of feature vectors.
y	A vector of target values.

predict()

std::vector< double > RandomForestRegressor::predict

(

const std::vector< std::vector< double >> &

X

)

const

Predicts target values for given input data.

Parameters

X	A vector of feature vectors.

Returns

A vector of predicted target values.

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The documentation for this class was generated from the following file:

• ml_library_include/ml/tree/RandomForestRegressor.hpp