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[D] Can someone answer some questions based on decision trees?

So I understand that you don’t need to scale features for a decision tree, since it will just find the right place to split on anyway. Do outliers need to be handled though? Does it matter if I have some features that have a way higher variance within it compared to others? Lastly, for categorical variables, I have my observations labeled in one of 5 labels (this is a feature, not the target). Will it adversely affect the results if the labels are imbalanced? I have one label that makes up roughly 60% of all the observations. Should I try to relabel things so it’s a little more balanced (I can collapse some of the other labels) Btw these questions are for either classification or regression trees.

submitted by /u/mydogissnoring
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.