Google Exam Professional-Machine-Learning-Engineer Topic 3 Question 33 Discussion

Actual exam question for Google's Google Professional Machine Learning Engineer exam

Question #: 33
Topic #: 3

[All Google Professional Machine Learning Engineer Questions]

You 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 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.

Show Suggested Answer

Suggested Answer: C

by Cristy at May 07, 2022, 07:46 AM

Limited Time Offer

25%

Off

Get Premium Professional-Machine-Learning-Engineer Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel

Currently there are no comments in this discussion, be the first to comment!