[M/K]Scaling have different affection on regression or decisiontree
Scaling have different affection on regression or decisiontree
Scaling is a necessary step of preprocessing,it can help eliminating the bias caused by variable with different scales. It works in SVM or LR,but not in DecisionTree Algorithms like RF,LGBM and XGB. The main reason that causes this difference is because DecisionTree algorithms’ working mechanism is to see how categorical variables differ,which is not like regression’s math issue. It does not rely on the scale of variables.
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