Q1. [1] § 3.3: Accuracy and Error § Reflection Time § Assertion and reasoning-based questions
Statement 1 : Overfitting is not recommended for evaluation of a model.
Statement 2 : This is because the model will simply remember the whole training set, and will therefore always predict the correct label for any point in the training set.
(A) Both Statement 1 and Statement 2 are correct.
(B) Both Statement 1 and Statement 2 are incorrect.
(C) Statement 1 is correct but Statement 2 is incorrect.
(D) Statement 2 is correct but Statement 1 is incorrect.
- (A) Both Statement 1 and Statement 2 are correct.
- (B) Both Statement 1 and Statement 2 are incorrect.
- (C) Statement 1 is correct but Statement 2 is incorrect.
- (D) Statement 2 is correct but Statement 1 is incorrect.
Previously asked in CBSE board exam
2024 104 Q4 (ii)
Generated by claude-sonnet-4-6 · 2026-06-21 03:18 · grounding rag
Model Answer
(A) Both Statement 1 and Statement 2 are correct.
Explanation
Overfitting means the model memorises training data, so it performs well on training data but poorly on unseen data — making it unsuitable for model evaluation. Both statements correctly describe this problem.
If a question refers to an image, map, graph or diagram that is not shown here, find the actual CBSE question paper on the CBSE website:
cbse.gov.in.