Does the solution meet the goal?

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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 (MDI) binning mode.

Does the solution meet the goal?
A . Yes
B . No

View Answer

Answer: A

Explanation:

Entropy MDL binning mode: This method requires that you select the column you want to predict and the column or columns that you want to group into bins. It then makes a pass over the data and attempts to determine the number of bins that minimizes the entropy. In other words, it chooses a number of bins that allows the data column to best predict the target column. It then returns the bin number associated with each row of your data in a column named <colname>quantized.

References:

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/group-data-into-bins