Python create_cv_id Examples

Example #1

File: binary.py Project: ikki407/stacking

        'nthread':8,'reg_lambda':3,'reg_alpha':0.01,
        'objective':'binary:logistic',
        'silent':1, 'subsample':0.60,
        }

class ModelV1_stage2(BaseModel):
        def build_model(self):
            return XGBClassifier(params=self.params, num_round=5)

# ----- END first stage stacking model -----

if __name__ == "__main__":
    
    # Create cv-fold index
    train = pd.read_csv(INPUT_PATH + 'train.csv')
    create_cv_id(train, n_folds_ = 5, cv_id_name='cv_id', seed=407)

    ######## stage1 Models #########
    print 'Start stage 1 training'

    m = ModelV1(name="v1_stage1",
                flist=FEATURE_LIST_stage1,
                params = PARAMS_V1,
                kind = 'st'
                )
    m.run()


    m = ModelV2(name="v2_stage1",
                flist=FEATURE_LIST_stage1,
                params = PARAMS_V2,

Example #2

        'objective':'reg:linear', 'seed':407,
        'silent':1, 'subsample':0.8
         }

class ModelV1_stage2(BaseModel):
        def build_model(self):
            return XGBRegressor(params=self.params, num_round=50)


# ----- END first stage stacking model -----

if __name__ == "__main__":
    
    # Create cv-fold index
    target = pd.read_csv(INPUT_PATH + 'target.csv')
    create_cv_id(target, n_folds_ = 5, cv_id_name='cv_id', seed=407)

    ######## stage1 Models #########
    print 'Start stage 1 training'

    m = ModelV1(name="v1_stage1",
                flist=FEATURE_LIST_stage1,
                params = PARAMS_V1,
                kind = 'st'
                )
    m.run()


    m = ModelV2(name="v2_stage1",
                flist=FEATURE_LIST_stage1,
                params = PARAMS_V2,

Example #3

    'subsample': 0.8
}


class ModelV1_stage2(BaseModel):
    def build_model(self):
        return XGBRegressor(params=self.params, num_round=50)


# ----- END first stage stacking model -----

if __name__ == "__main__":

    # Create cv-fold index
    train = pd.read_csv(INPUT_PATH + 'train.csv')
    create_cv_id(train, n_folds_=5, cv_id_name='cv_id', seed=407)

    ######## stage1 Models #########
    print 'Start stage 1 training'

    m = ModelV1(name="v1_stage1",
                flist=FEATURE_LIST_stage1,
                params=PARAMS_V1,
                kind='st')
    m.run()

    m = ModelV2(name="v2_stage1",
                flist=FEATURE_LIST_stage1,
                params=PARAMS_V2,
                kind='st')
    m.run()