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erdogant / hgboost

hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating the results on an independent validation set. hgboost can be applied for classification and regression tasks.
http://erdogant.github.io/hgboost
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Error in rmse calculaiton #3

Closed SSLPP closed 3 years ago

SSLPP commented 3 years ago 
if self.eval_metric=='rmse':
                loss = mean_squared_error(y_test, y_pred)

mean_squared_error in sklearn gives mse, use mean_squared_error(y_true, y_pred, squared=False) for rmse

erdogant commented 3 years ago

Thank you for mentioning this point. I fixed the mse and rmse usage and released a new version.

Update with:

pip install -U hgboost

Check the version, should be >= 0.1.7

import hgboost
print(hgboost.__version__)