Johnne32

params_xgb = {
    'learning_rate': [.1, .05, ],
    'colsample_bytree': [.3, .4, .5, .6],
    'max_depth': [1],
    'alpha': [3],
    'subsample': [.5],
    'n_estimators': [30, 70, 100, 200]
}

xgb_model = XGBRegressor()

Johnne32

# Import label encoder 
from sklearn import preprocessing   
label_encoder = preprocessing.LabelEncoder() 
final_df['Type']= label_encoder.fit_transform(final_df['Type'])
final_df['City Group']= label_encoder.fit_transform(final_df['City Group'])
final_df.head()