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I carried out a grid search on my xgboost and varied the parameters below. I noticed in my grid search results that the train score is very high, e.g. 0.99999 and my test scores are more modest around 0.72. Since there is such a big difference between my train and test score does this indicate over fitting?

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I assume your score is a metric like accuracy, f1-score etc. If that is the case, yes, it quite certainly indicates overfitting. 28% accuracy difference between train and test/validation is very high, and it means the model didn't generalise as well for the test set as the training set.

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  • $\begingroup$ what if i am also doing a grid search on say brier score, how can i tell over fitting? $\endgroup$
    – mathella
    Commented Aug 10, 2020 at 16:21
  • $\begingroup$ It still is large. It's also interesting to see that your scores don't change wrt hyperparameter changes $\endgroup$
    – gunes
    Commented Aug 10, 2020 at 19:52

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