Question

imagine you have just finished training a decision tree for spam classication and it is showing abnormal bad performance on both your training and test sets. assume that your implementation has no bugs. what could be reason for this problem

Answer 1

Please find the answer below:

Keeping in view that you have just finished training a decision tree for spam classification and it is showing abnormal bad performance on both your training and test sets. assume that your implementation has no bugs.

Unsupervised learning could be reason for this problem.

Answer 2

   The abnormal bad performance on training and tests after immediate training for classification of spam and implementation has no bugs, in that case lack of supervision or vague supervision or any other bug in supervision can be one of the major reasons.

     Irregularity in training or fault in conveying the training in same or concurrent terms may also be the reason.