You just finished training a decision tree for spam classification, and it is gettingabnormally bad performance on both your training and test sets. you know that yourimplementation has no bugs, so what could be causing the problem?

(a) your decision trees are too shallow.
(b) you need to increase the learning rate.
(c) you are overfitting.
(d) all of the above

Option B is the correct option.

Explanation:

The following answer is true because when the person completed our training of a decision tree and after the following presentation he getting not good working performance on both side i.e., test sets and during the training period. After the training there is no bug on the implementation of the presentation then, he has to increase the rate of the learning.

i do not get the question.