DecisionTreeRegressor Class Reference

Implements a Decision Tree Regressor. More...

#include <DecisionTreeRegressor.hpp>

Public Member Functions
	DecisionTreeRegressor (int max_depth=5, int min_samples_split=2)
	Constructs a DecisionTreeRegressor. More...
	~DecisionTreeRegressor ()
	Destructor for DecisionTreeRegressor.
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 Decision Tree Regressor.

Constructor & Destructor Documentation

DecisionTreeRegressor()

DecisionTreeRegressor::DecisionTreeRegressor	(	int	max_depth = 5,
		int	min_samples_split = 2
	)

Constructs a DecisionTreeRegressor.

Parameters

max_depth	The maximum depth of the tree.
min_samples_split	The minimum number of samples required to split an internal node.

Member Function Documentation

fit()

void DecisionTreeRegressor::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 > DecisionTreeRegressor::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/DecisionTreeRegressor.hpp