Cpp ML Library
1.0.0
A library of Machine Learning Algorithmns seen from the Udemy course Machine Learning A to Z.
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Implements a Decision Tree Classifier. More...
#include <DecisionTreeClassifier.hpp>
Public Member Functions | |
DecisionTreeClassifier (int max_depth=5, int min_samples_split=2) | |
Constructs a DecisionTreeClassifier. More... | |
~DecisionTreeClassifier () | |
Destructor for DecisionTreeClassifier. | |
void | fit (const std::vector< std::vector< double >> &X, const std::vector< int > &y) |
Fits the model to the training data. More... | |
std::vector< int > | predict (const std::vector< std::vector< double >> &X) const |
Predicts class labels for given input data. More... | |
Implements a Decision Tree Classifier.
DecisionTreeClassifier::DecisionTreeClassifier | ( | int | max_depth = 5 , |
int | min_samples_split = 2 |
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) |
Constructs a DecisionTreeClassifier.
max_depth | The maximum depth of the tree. |
min_samples_split | The minimum number of samples required to split an internal node. |
void DecisionTreeClassifier::fit | ( | const std::vector< std::vector< double >> & | X, |
const std::vector< int > & | y | ||
) |
Fits the model to the training data.
X | A vector of feature vectors. |
y | A vector of target class labels. |
std::vector< int > DecisionTreeClassifier::predict | ( | const std::vector< std::vector< double >> & | X | ) | const |
Predicts class labels for given input data.
X | A vector of feature vectors. |