If the dependent variable has both positive and negative values, how to approach any machine learning algorithm?
I can't think of any machine learning algorithms that can't handle both positive and negative values. The scoring should still be accurate. If you would like to take the log transform of a column with negative values, then you can add some large constant to the column that makes all values positive and then take the log.
If the dependent variable has both positive and negative values, the model.score of any regression models are not accurate when train and test score are compared. I tried converting the target column into log but since there are negative values as well, it seems this is not right. Please advise