#
# mean_predict = SimplePredict(True)
# mean_predict.run_all()
#
# linear_predict = LinearPredict()
# linear_predict.run_all()
#
# filter_linear_predict = FilterLinearPredict(3)
# filter_linear_predict.run_all()
#
# params = {'n_estimators': 250, 'max_depth': 3, 'min_samples_split': 1,
# 'learning_rate': 0.001, 'loss': 'lad'}
# gradient_boost = FilterGradientBoostPredict(params, 4)
# gradient_boost.run_all()
#param = {'max_depth':3, 'eta':1.0, 'objective':'reg:linear'}
#xgboost_predict = XGBoostPredict(param)
#xgboost_predict.run_all()
#
# param = {'max_depth':3, 'eta':1.0, 'objective':'reg:linear', 'range':4}
# filter_xgboost_predict = FilterXGBoostPredict(param)
# filter_xgboost_predict.run_all()
if __name__ == '__main__':
#RunAnalysis()
#RunForcast()
RunAnalysis()
param = {'max_depth':3, 'eta':1.0, 'objective':'reg:linear'}
xgboost_predict = XGBoostPredict(param)
xgboost_predict.run_all()
