Question 72 of 280
Single answerYou are building a linear model with over 100 input features, all with values between –1 and 1. You suspect that
many features are non-informative. You want to remove the non-informative features from your model while
keeping the informative ones in their original form. Which technique should you use?
AUse principal component analysis (PCA) to eliminate the least informative features.
✓BUse L1 regularization to reduce the coefficients of uninformative features to 0.
CAfter building your model, use Shapley values to determine which features are the most informative.
DUse an iterative dropout technique to identify which features do not degrade the model when removed.
✓
Correct Answer: B
Use L1 regularization to reduce the coefficients of uninformative features to 0.
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Explanation
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