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I don't know the efficient method to select the best subset of the estimator that saves time and highest accuracy. How to choose the best estimators for the Voting classifier?

Voting Classifier is an ensemble technique for combines the predictions of several underlying machine learning models (estimators). It makes a final prediction based on either majority voting ("hard") or averaging probabilities ("soft"). Example: I have 20 estimators. I want to select the subset of these estimators that achieve the highest accuracy by saving time.

dataset: https://drive.google.com/file/d/1lcfDLwnJ1TVQfGbn7x0LrZwaWRonP57Z/view?usp=sharing

target: term_grade

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  • $\begingroup$ Please provide more information on the packages and models you are using as well as information about your dataset. This will help others gain more context about your specific problem and question. Thanks! $\endgroup$
    – RegressIt
    Mar 12 at 20:37
  • $\begingroup$ Voting Classifier is an ensemble technique for combines the predictions of several underlying machine learning models (estimators). It makes a final prediction based on either majority voting ("hard") or averaging probabilities ("soft"). Example: I have 20 estimators. I want to select the subset of these estimators that achieve the highest accuracy by saving time. $\endgroup$
    – Davann Tet
    Mar 14 at 2:58
  • $\begingroup$ dataset: drive.google.com/file/d/1lcfDLwnJ1TVQfGbn7x0LrZwaWRonP57Z/… target: term_grade $\endgroup$
    – Davann Tet
    Mar 14 at 3:10

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