Pre-Winter Sale Limited Time 65% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: pass65

Google Professional Data Engineer Exam Professional-Data-Engineer Question # 51 Topic 6 Discussion

Google Professional Data Engineer Exam Professional-Data-Engineer Question # 51 Topic 6 Discussion

Professional-Data-Engineer Exam Topic 6 Question 51 Discussion:
Question #: 51
Topic #: 6

You are building a model to predict whether or not it will rain on a given day. You have thousands of input features and want to see if you can improve training speed by removing some features while having a minimum effect on model accuracy. What can you do?


A.

Eliminate features that are highly correlated to the output labels.


B.

Combine highly co-dependent features into one representative feature.


C.

Instead of feeding in each feature individually, average their values in batches of 3.


D.

Remove the features that have null values for more than 50% of the training records.


Get Premium Professional-Data-Engineer Questions

Contribute your Thoughts:


Chosen Answer:
This is a voting comment (?). It is better to Upvote an existing comment if you don't have anything to add.