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1 vote

How do I identify overffiting when using GridSchearCV?

I assume this 'mean_test_score' corresponds to the mean validation score [...]. So, I assume these scores: Training score = 'mean_train_score' Validation score = 'mean_test_score' Test score = score ...
MuhammedYunus's user avatar
0 votes

Scoring function in cross-validation often left default

It does sound a bit inconsistent to me, and in usual circumstances I'd probably opt for a different strategy. Tuning the model for accuracy suggests that accuracy is the metric of importance for the ...
MuhammedYunus's user avatar
2 votes

How an I improve my prediction of my model much more than that?

The first thing I can notice is that your followers feature ranges from $0$ to $10^6$. You would want to first make your regression on a logarithmic scale: ...
Yann's user avatar
  • 21
0 votes

Is it usual to obtain very different values of mutual information score using sci-kit learn?

It is not unusual to see decreasing discrete MI estimates with increasing sample number, because of estimator bias in the sparsely sampled regime. In practice, sparse sampling is often due to having ...
ggggg's user avatar
  • 1
1 vote

Making cpp function from xgboost dump_model() output

I'm not sure entirely why this works... but if I explicitly set base_score = 0.5 in xgb.XGBClassifier then everything works. As ...
Miles Cochran-Branson's user avatar
3 votes

Linear regression with confidence interval

You can refer to the mapie library that provides a solution to your requirements. I am providing a link to the official documentation of mapie library, that will give you code examples of ...
Praneeth's user avatar

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