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. High bias indicates that the model is overly simplistic and fails to capture the complexity of the data, resulting in underfitting. - (B): True. High variance indicates that the model is overly complex, fitting noise in the training data, which leads to overfitting. - (C): False. High bias does not cause overfitting; it leads to underfitting. - (D): True. Bias and variance are inversely proportional; reducing one often increases the other.