pmlpp/test/mlpp_tests.h

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#ifndef MLPP_TESTS_H
#define MLPP_TESTS_H
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// TODO port this class to use the test module once it's working
// Also don't forget to remove it's bindings
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#include "core/math/math_defs.h"
#include "core/containers/vector.h"
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#include "core/object/reference.h"
#include "core/string/ustring.h"
class MLPPMatrix;
class MLPPVector;
class MLPPTests : public Reference {
GDCLASS(MLPPTests, Reference);
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public:
void test_statistics();
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void test_linear_algebra();
void test_univariate_linear_regression();
void test_multivariate_linear_regression_gradient_descent(bool ui = false);
void test_multivariate_linear_regression_sgd(bool ui = false);
void test_multivariate_linear_regression_mbgd(bool ui = false);
void test_multivariate_linear_regression_normal_equation(bool ui = false);
void test_multivariate_linear_regression_adam();
void test_multivariate_linear_regression_score_sgd_adam(bool ui = false);
void test_multivariate_linear_regression_epochs_gradient_descent(bool ui = false);
void test_multivariate_linear_regression_newton_raphson(bool ui = false);
void test_logistic_regression(bool ui = false);
void test_probit_regression(bool ui = false);
void test_c_log_log_regression(bool ui = false);
void test_exp_reg_regression(bool ui = false);
void test_tanh_regression(bool ui = false);
void test_softmax_regression(bool ui = false);
void test_support_vector_classification(bool ui = false);
void test_mlp(bool ui = false);
void test_soft_max_network(bool ui = false);
void test_autoencoder(bool ui = false);
void test_dynamically_sized_ann(bool ui = false);
void test_wgan(bool ui = false);
void test_ann(bool ui = false);
void test_dynamically_sized_mann(bool ui = false);
void test_train_test_split_mann(bool ui = false);
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void test_naive_bayes();
void test_k_means(bool ui = false);
void test_knn(bool ui = false);
void test_convolution_tensors_etc();
void test_pca_svd_eigenvalues_eigenvectors(bool ui = false);
void test_nlp_and_data(bool ui = false);
void test_outlier_finder(bool ui = false);
void test_new_math_functions();
void test_positive_definiteness_checker();
void test_numerical_analysis();
void test_support_vector_classification_kernel(bool ui = false);
void test_mlpp_vector();
void test_mlpp_matrix();
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void is_approx_equalsd(real_t a, real_t b, const String &str);
void is_approx_equals_dvec(const Vector<real_t> &a, const Vector<real_t> &b, const String &str);
void is_approx_equals_dmat(const Vector<Vector<real_t>> &a, const Vector<Vector<real_t>> &b, const String &str);
void is_approx_equals_mat(Ref<MLPPMatrix> a, Ref<MLPPMatrix> b, const String &str);
void is_approx_equals_vec(Ref<MLPPVector> a, Ref<MLPPVector> b, const String &str);
MLPPTests();
~MLPPTests();
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protected:
static void _bind_methods();
String _breast_cancer_data_path;
String _breast_cancer_svm_data_path;
String _california_housing_data_path;
String _fires_and_crime_data_path;
String _iris_data_path;
String _mnist_test_data_path;
String _mnist_train_data_path;
String _wine_data_path;
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};
#endif