Dec 31, 2019 in Data Science

Suppose you are training a linear regression model. Now consider these points.

  1. Overfitting is more likely if we have less data
  2. Overfitting is more likely when the hypothesis space is small

Which of the above statement(s) are correct?

A. Both are False

B. 1 is False and 2 is True

C. 1 is True and 2 is False

D. Both are True

1 Answer

0 votes
Dec 31, 2019

Solution: C

1.With small training dataset, it’s easier to find a hypothesis to fit the training data exactly i.e. overfitting.

2. We can see this from the bias-variance trade-off. When hypothesis space is small, it has higher bias and lower variance. So with a small hypothesis space, it’s less likely to find a hypothesis to fit the data exactly i.e. underfitting.

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