Exam DP-100 topic 1 question 17 discussion

Actual exam question from Microsoft's DP-100

Question #: 17
Topic #: 1

You need to consider the underlined segment to establish whether it is accurate.
To transform a categorical feature into a binary indicator, you should make use of the Clean Missing Data module.
Select `No adjustment required` if the underlined segment is accurate. If the underlined segment is inaccurate, select the accurate option.

A. No adjustment required.
B. Convert to Indicator Values
C. Apply SQL Transformation
D. Group Categorical Values

Show Suggested Answer

Suggested Answer: B 🗳️

by synapse at March 12, 2022, 10:37 a.m.

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Peeking

Highly Voted 2 years ago

Selected Answer: B

This is equivalent to one-hot encoding of a categorical column

upvoted 6 times

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Sjefen

Highly Voted 2 years, 10 months ago

Correct

upvoted 5 times

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lianaliam

Most Recent 2 months ago

Selected Answer: A

OHC for categirical column

upvoted 1 times

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Lion007

1 year, 1 month ago

Selected Answer: B

The answer is correct. B "....the Convert to Indicator Values module in Machine Learning Studio (classic). The purpose of this module is to convert columns that contain categorical values into a series of binary indicator columns that can more easily be used as features in a machine learning model." See https://learn.microsoft.com/en-us/previous-versions/azure/machine-learning/studio-module-reference/convert-to-indicator-values

upvoted 2 times

Lion007

1 year, 1 month ago

Usage tips >> If the column contains missing values, a separate indicator column is created for the missing category, with this name: <source column>- Missing See https://learn.microsoft.com/en-us/previous-versions/azure/machine-learning/studio-module-reference/convert-to-indicator-values#usage-tips

upvoted 1 times

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