Answer-first summary for fast verification
Answer: Yes
The solution meets the goal because Quantiles normalization with QuantileIndex normalization effectively bins values for prediction. Quantiles normalization divides data into equal-sized intervals (quantiles), and QuantileIndex normalization assigns each value to a quantile index (e.g., 1 to number of bins), producing a binned output column. This is supported by Azure ML documentation and community consensus (e.g., the highest upvoted comment with 29 upvotes confirms this approach). While some comments incorrectly suggest using Entropy MDL (which considers the target column for binning), the question only requires binning an input feature to predict a target, not using the target for binning itself. Thus, 'A' is correct.
Author: LeetQuiz Editorial Team
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You are a data scientist using Azure Machine Learning Studio. You need to normalize values into bins to predict a target column.
Solution: Apply a Quantiles normalization with a QuantileIndex normalization.
Does the solution meet the goal?
A
Yes
B
No
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