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Exam DP-100 topic 3 question 33 discussion

Actual exam question from Microsoft's DP-100
Question #: 33
Topic #: 3
[All DP-100 Questions]

You plan to use automated machine learning to train a regression model. You have data that has features which have missing values, and categorical features with few distinct values.
You need to configure automated machine learning to automatically impute missing values and encode categorical features as part of the training task.
Which parameter and value pair should you use in the AutoMLConfig class?

  • A. featurization = 'auto'
  • B. enable_voting_ensemble = True
  • C. task = 'classification'
  • D. exclude_nan_labels = True
  • E. enable_tf = True
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Suggested Answer: A 🗳️
by ljljljlj at July 11, 2021, 2:04 p.m.

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datamijn
Highly Voted 3 years, 3 months ago
on 2/8/2021
upvoted 8 times
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Moshekwa
Highly Voted 3 years, 3 months ago
Chosen Answer is correct " In every automated machine learning experiment, automatic scaling and normalization techniques are applied to your data by default. These techniques are types of featurization that help certain algorithms that are sensitive to features on different scales. You can enable more featurization, such as missing-values imputation, encoding, and transforms." Source: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-configure-auto-features
upvoted 6 times
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evangelist
Most Recent 5 months ago
Selected Answer: A
given answer is correct featurization =on is must
upvoted 1 times
...
fhlos
1 year, 4 months ago
Selected Answer: A
A - ChatGPT
upvoted 1 times
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synapse
2 years, 7 months ago
Selected Answer: A
AutoFeaturization takes care of this. A
upvoted 2 times
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[Removed]
2 years, 8 months ago
On 20Feb2022
upvoted 3 times
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snsnsnsn
3 years, 2 months ago
on 2/9/21
upvoted 4 times
...
ljljljlj
3 years, 3 months ago
On exam 2021/7/10
upvoted 6 times
...
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