def train(self): """ ## Train Single Model ## Model Name: 'lr': Logistic Regression 'rf': Random Forest 'et': Extra Trees 'gb': GradientBoosting 'xgb': XGBoost 'xgb_sk': XGBoost using scikit-learn module 'lgb': LightGBM 'lgb_sk': LightGBM using scikit-learn module 'cb': CatBoost """ TM = TrainingMode() """ Global Seed """ train_seed = random.randint(0, 1000) cv_seed = random.randint(0, 1000) # train_seed = 666 # cv_seed = 216 # 425 48 461 157 """ Training Arguments """ train_args = {'use_global_valid': False, 'use_custom_obj': False, 'show_importance': False, 'save_final_pred': True, 'save_final_pred_train': False, 'save_cv_pred': True, 'save_cv_pred_train': False, 'save_csv_log': True, 'loss_fuc': self.rmse, 'append_info': 'Yuanan Bike'} """ Cross Validation Arguments """ cv_args = {'n_cv': 10} """ Base Parameters """ base_parameters = self.get_base_params('dnn') """ Train Single Model """ TM.train_single_model('dnn', train_seed, cv_seed, # num_boost_round=1000, base_parameters=base_parameters, train_args=train_args, cv_args=cv_args) print('======================================================') print('Global Train Seed: {}'.format(train_seed)) print('Global Cross Validation Seed: {}'.format(cv_seed))
def train(self): """ ## Train Single Model ## Model Name: 'lr': Logistic Regression 'rf': Random Forest 'et': Extra Trees 'ab': AdaBoost 'gb': GradientBoosting 'xgb': XGBoost 'xgb_sk': XGBoost using scikit-learn module 'lgb': LightGBM 'lgb_sk': LightGBM using scikit-learn module 'cb': CatBoost 'dnn': Deep Neural Networks 'stack_lgb': LightGBM for stack layer 'christar': Christar1991 'prejudge_b': PrejudgeBinary 'prejudge_m': PrejudgeMultiClass 'stack_t': StackTree """ TM = TrainingMode() """ Global Seed """ train_seed = random.randint(0, 1000) cv_seed = random.randint(0, 1000) # train_seed = 666 # cv_seed = 216 # 425 48 461 157 """ Training Arguments """ train_args = {'prescale': False, 'postscale': True, 'use_scale_pos_weight': False, 'use_global_valid': False, 'use_custom_obj': False, 'show_importance': False, 'show_accuracy': False, 'save_final_pred': True, 'save_final_prob_train': False, 'save_cv_pred': False, 'save_cv_prob_train': False, 'save_csv_log': True, 'append_info': 'fw_v0.2_c20_w35'} """ Cross Validation Arguments """ # cv_args = {'n_valid': 4, # 'n_cv': 20, # 'n_era': 20} cv_args = self.get_cv_args('lgb_fi') """ Reduced Features """ reduced_feature_list = None """ Base Parameters """ base_parameters = self.get_base_params('lgb') # base_parameters = None """ Train Single Model """ TM.train_single_model('lgb', train_seed, cv_seed, num_boost_round=100, reduced_feature_list=reduced_feature_list, base_parameters=base_parameters, train_args=train_args, cv_args=cv_args, use_multi_group=True) print('======================================================') print('Global Train Seed: {}'.format(train_seed)) print('Global Cross Validation Seed: {}'.format(cv_seed))