def test_k_nearest_neighbor(self): self.assertTrue(expr=isinstance(Classification().k_nearest_neighbor(), KNeighborsClassifier))
def test_gradient_boosting_tree(self): self.assertTrue( expr=isinstance(Classification().gradient_boosting_tree(), GradientBoostingClassifier))
def test_gradient_boosting_tree_param(self): _gbo_param: dict = Classification().gradient_boosting_tree_param() self.assertTrue( expr=_gbo_param.get(list(_gbo_param.keys())[0]) != Classification( ).gradient_boosting_tree_param().get(list(_gbo_param.keys())[0]))
def test_cat_boost_param(self): _cat_boost_param: dict = Classification().cat_boost_param() self.assertTrue(expr=_cat_boost_param.get( list(_cat_boost_param.keys())[0]) != Classification( ).cat_boost_param().get(list(_cat_boost_param.keys())[0]))
def test_extreme_gradient_boosting_tree(self): self.assertTrue(expr=isinstance( Classification().extreme_gradient_boosting_tree(), XGBClassifier))
def test_linear_discriminant_analysis_param(self): _lda_param: dict = Classification().linear_discriminant_analysis_param( ) self.assertTrue(expr=_lda_param.get(list(_lda_param.keys( ))[0]) != Classification().linear_discriminant_analysis_param().get( list(_lda_param.keys())[0]))
def test_quadratic_discriminant_analysis(self): self.assertTrue( expr=isinstance(Classification().quadratic_discriminant_analysis(), QuadraticDiscriminantAnalysis))
def test_nu_support_vector_machine_param(self): _nusvm_param: dict = Classification().nu_support_vector_machine_param() self.assertTrue(expr=_nusvm_param.get(list(_nusvm_param.keys())[0]) != Classification().nu_support_vector_machine_param().get( list(_nusvm_param.keys())[0]))
def test_ada_boosting(self): self.assertTrue(expr=isinstance(Classification().ada_boosting(), AdaBoostClassifier))
def test_linear_support_vector_machine(self): self.assertTrue(expr=isinstance( Classification().linear_support_vector_machine(), LinearSVC))
def test_nu_support_vector_machine(self): self.assertTrue(expr=isinstance( Classification().nu_support_vector_machine(), NuSVC))
def test_random_forest_param(self): _rf_param: dict = Classification().random_forest_param() self.assertTrue( expr=_rf_param.get(list(_rf_param.keys())[0]) != Classification( ).random_forest_param().get(list(_rf_param.keys())[0]))
def test_random_forest(self): self.assertTrue(expr=isinstance(Classification().random_forest(), RandomForestClassifier))
def test_quadratic_discriminant_analysis_param(self): _qda_param: dict = Classification( ).quadratic_discriminant_analysis_param() self.assertTrue(expr=_qda_param.get(list(_qda_param.keys( ))[0]) != Classification().quadratic_discriminant_analysis_param().get( list(_qda_param.keys())[0]))
def test_k_nearest_neighbor_param(self): _knn_param: dict = Classification().k_nearest_neighbor_param() self.assertTrue( expr=_knn_param.get(list(_knn_param.keys())[0]) != Classification( ).k_nearest_neighbor_param().get(list(_knn_param.keys())[0]))
def test_ada_boosting_param(self): _ada_boost_param: dict = Classification().ada_boosting_param() self.assertTrue(expr=_ada_boost_param.get( list(_ada_boost_param.keys())[0]) != Classification( ).ada_boosting_param().get(list(_ada_boost_param.keys())[0]))
def test_linear_discriminant_analysis(self): self.assertTrue( expr=isinstance(Classification().linear_discriminant_analysis(), LinearDiscriminantAnalysis))
def test_cat_boost(self): self.assertTrue( expr=isinstance(Classification().cat_boost(), CatBoostClassifier))
def test_logistic_regression(self): self.assertTrue(expr=isinstance(Classification().logistic_regression(), LogisticRegression))
def test_logistic_regression_param(self): _logistic_param: dict = Classification().logistic_regression_param() self.assertTrue(expr=_logistic_param.get( list(_logistic_param.keys())[0]) != Classification( ).logistic_regression_param().get(list(_logistic_param.keys())[0]))