MACHINE LEARNING
INTRODUCTION
Question
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Adding a nonimportant feature to a linear regression model may result in.1.Increase in MSE2.Decrease in Rsquare

1


2


1 and 2


none of these

Explanation:
Detailed explanation1: As we increase the size of the training data, the bias would increase while the variance would decrease.
Detailed explanation2: Higher values of K will result in higher confidence on the crossvalidation result as compared to lower value of K. If K=N, then it is called Leave one out cross validation, where N is the number of observations.
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