As the title states, when I add another feature to the previous 200+ ones, the algorithm starts to train about 10 minutes, while earlier it trained only for a minute.
Can anybody please explain me why this can happen?
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There is too few information to give a reasonable answer to this question, my thoughts is that the feature you are adding is a categorical variable presumably with a vast amount of different categories, what would increase the X matrix dimension (if using one hot encoding) thus increasing training time.