Question

Which is/are true about bias and variance?
(A) High bias means that the model is underfitting.
(B) High variance means that the model is overfitting.
(C) High bias means that the model is overfitting.
(D) Bias and variance are inversely proportional to each other.
Choose the correct answer from the options given below:

• A. (B), (C) and (D) only.
• B. (B) and (D) only.
• C. (A), (B) and (D) only.
• D. (C) and (D) only.

Hint:

Use the bias-variance tradeoff to understand the balance between underfitting and overfitting.

Answer 1

The Correct Option is C

- (A): True. A model with high bias is too simplistic, failing to capture data complexity, which results in underfitting. - (B): True. High variance means the model is excessively complex, fitting noise in the training data and leading to overfitting. - (C): False. High bias leads to underfitting, not overfitting. - (D): True. Bias and variance are inversely proportional; a reduction in one often causes an increase in the other.