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Anshul Vohra
Anshul Vohra

Anshul Vohra

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From Boosting the accuracy of your Machine Learning models by Prashant Gupta

…op in the error function for a variable at each split point gives us an idea of feature importance. It means that we record the total amount that the error is decreased due to splits over a given predictor, averaged over all bagged trees. A large value then indicates an important predictor. In regression problems this may be the drop in residual sum of squares and in classification this might be the Gini score.

From Boosting the accuracy of your Machine Learning models by Prashant Gupta

If m = p then random forests is equal to bagging.

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