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]))