Does class_weight solve unbalanced input for Decision Tree? I've read in sklearn's documentation that we have to take special care in balancing the input for a decision tree, but it doesn't tell you what function to use. However, I've found the parameter class_weight. If I use class_weight: balanced as a parameter, will that mean that I can omit balancing the input by hand?
Yes you don't need to balance your train data by hand. But your test data can still be (truly) unbalanced.