def test_save_prediction(self): model = RandomForestClassifier() model.id = get_model_id(model) model.fit(self.iris.data, self.iris.target) indexes = np.fromfunction(lambda x: x, (self.iris.data.shape[0], ), dtype=np.int32) saving_predict_proba(model, self.iris.data, indexes) os.remove('RandomForestClassifier_r0_N__m5_0p0__m4_2__m1_auto__m0_N__m3_1__m2_N__n0_10__b0_1__c1_gini__c0_N_0_149.csv')
def test_save_prediction(self): model = RandomForestClassifier() model.id = get_model_id(model) model.fit(self.iris.data, self.iris.target) indexes = np.fromfunction(lambda x: x, (self.iris.data.shape[0], ), dtype=np.int32) saving_predict_proba(model, self.iris.data, indexes) os.remove('RandomForestClassifier_r0_N__m5_0p0__m4_2__m1_auto__m0_N__m3_1__m2_N__n0_10__b0_1__c1_gini__c0_N_190.csv')
def test_save_prediction(self): model = RandomForestClassifier() model.id = get_model_id(model) model.fit(self.iris.data, self.iris.target) indexes = np.fromfunction(lambda x: x, (self.iris.data.shape[0], ), dtype=np.int32) saving_predict_proba(model, self.iris.data, indexes) any_file_removed = False for filename in os.listdir('.'): if filename.startswith('RandomForestClassifier'): os.remove(filename) any_file_removed = True self.assertTrue(any_file_removed)