faster_ml/algorithms.h at main · SanBast/faster_ml · GitHub

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#ifndef ALGORITHMS_H
#define ALGORITHMS_H

#include "ml_headers.h"

// Utility functions
Dataset* create_dataset(int n_samples, int n_features);
void free_dataset(Dataset *ds);
double dot_product(double *a, double *b, int n);
void matrix_vector_mult(double **A, double *x, double *result, int rows, int cols);
int validate_dataset(Dataset *ds);

// Linear Regression
LinearRegression* create_linear_regression(int n_features);
void train_linear_regression(LinearRegression *lr, Dataset *ds, double learning_rate, int epochs);
double predict_linear_regression(LinearRegression *lr, double *sample);
void free_linear_regression(LinearRegression *lr);

// Ridge Regression
RidgeRegression* create_ridge_regression(int n_features, double alpha);
void train_ridge_regression(RidgeRegression *rr, Dataset *ds, double learning_rate, int epochs);
double predict_ridge_regression(RidgeRegression *rr, double *sample);
void free_ridge_regression(RidgeRegression *rr);

// K-Nearest Neighbors
KNN* create_knn(int k);
void train_knn(KNN *knn, Dataset *ds);
double predict_knn_regression(KNN *knn, double *sample);
int predict_knn_classification(KNN *knn, double *sample);
void free_knn(KNN *knn);

// Random Forest
RandomForest* create_random_forest(int n_trees, int max_depth, int min_samples_split);
void train_random_forest(RandomForest *rf, Dataset *ds);
double predict_random_forest(RandomForest *rf, double *sample);
void free_random_forest(RandomForest *rf);

// XGBoost
XGBoost* create_xgboost(int n_trees, double learning_rate, int max_depth);
void train_xgboost(XGBoost *xgb, Dataset *ds);
double predict_xgboost(XGBoost *xgb, double *sample);
void free_xgboost(XGBoost *xgb);

#endif // ALGORITHMS_H