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I implemented a Bagging Ensemble model in sklearn, but the cross_validate method always returns a perfect train score. Here is my code

And here are my results enter image description here

Is this behaviour normal or am I doing something wrong in my implementation?

Micu
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  • Perfect training metrics *do not* mean overfitting. The problem could just be easy. The problem is berry high train metrics ve low test metrics, we would treat this as a sign of overfitting. If you have a perfect training score and a high (?) test score, you should be happy about the result. Any reason to believe that the 88% accuracy is a bad result? Keep in mind that accuracy is a poor metric https://stats.stackexchange.com/questions/312780/why-is-accuracy-not-the-best-measure-for-assessing-classification-models – Tim Jul 01 '21 at 10:05

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