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Question 83 - Professional Data Engineer discussion

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Which of the following are feature engineering techniques? (Select 2 answers)

A.
Hidden feature layers
Answers
A.
Hidden feature layers
B.
Feature prioritization
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B.
Feature prioritization
C.
Crossed feature columns
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C.
Crossed feature columns
D.
Bucketization of a continuous feature
Answers
D.
Bucketization of a continuous feature
Suggested answer: C, D

Explanation:

Selecting and crafting the right set of feature columns is key to learning an effective model.

Bucketization is a process of dividing the entire range of a continuous feature into a set of consecutive bins/buckets, and then converting the original numerical feature into a bucket ID (as a categorical feature) depending on which bucket that value falls into.

Using each base feature column separately may not be enough to explain the data. To learn the differences between different feature combinations, we can add crossed feature columns to the model.

Reference:

https://www.tensorflow.org/tutorials/wide#selecting_and_engineering_features_for_the_model

asked 18/09/2024
Harry Meijer
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