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Microsoft

DP-100 · Question #51

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might…

The correct answer is A. Yes. Entropy Minimum Description Length (MDL) is a supervised binning method available in Azure Machine Learning Studio's 'Group Data into Bins' module. It uses information theory to determine optimal bin boundaries based on the target variable, grouping continuous values into…

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Question

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You are using Azure Machine Learning Studio to perform feature engineering on a dataset. You need to normalize values to produce a feature column grouped into bins. Solution: Apply an Entropy Minimum Description Length (MDL) binning mode. Does the solution meet the goal?

Options

  • AYes
  • BNo

How the community answered

(28 responses)
  • A
    86% (24)
  • B
    14% (4)

Explanation

Entropy Minimum Description Length (MDL) is a supervised binning method available in Azure Machine Learning Studio's 'Group Data into Bins' module. It uses information theory to determine optimal bin boundaries based on the target variable, grouping continuous values into discrete bins (categories). This directly meets the goal of normalizing values to produce a feature column grouped into bins, so the solution is correct.

Topics

#Feature Engineering#Data Transformation#Azure Machine Learning Studio#Binning

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