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))