2
$\begingroup$

This question already has an answer here:

Is it important to scale all the features into a common range (normalized) when using random forests (bagging) in classification. Or can random forests handle features in different ranges without problems (bias to the larger values). Some features may have a value in the 1000-range and others in the 0-1 range.

$\endgroup$

marked as duplicate by Firebug, mdewey, whuber Sep 5 '18 at 16:32

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

0
$\begingroup$

Partially answered in comments:

There are similar questions on StackOverflow (https://stackoverflow.com/questions/8961586/do-i-need-to-normalize-or-scale-data-for-randomforest-r-package) and Quora (https://www.quora.com/Machine-Learning/Should-inputs-to-random-forests-be-normalized?srid=3EJy&st=ns). The short answer is that you don't. – tchakravarty

$\endgroup$

Not the answer you're looking for? Browse other questions tagged or ask your own question.