Which of these is NOT true about the evaluation of decision tree performance? (A) Performance on the training dataset ca...
Which of these is NOT true about the evaluation of decision tree
performance?
(A) Performance on the training dataset can overestimate
performance on future data
(B) Decision trees sometimes overfit the training data
(C) Creating a test dataset simulates the model's performance on unseen data
(D) The model's accuracy is unaffected by the rarity of the outcome.
Homework Answers
Please don't hesitate to give a "thumbs up" for the answer in case the answer has helped you
A, B and C are correct statements
D - is true. The rarer the event, the more likely the event' representation is captured / taken care off by the statistical model. If the model is not able to find the required representation then the model' accuracy is effected by the rarity of the outcome.
If there are many of these rare events, then the model' accuracy goes for a toss
D is correct
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