DP-100 · Question #75
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 B. No. Quantiles normalization with QuantileIndex is a data normalization technique that rescales feature values so they follow a uniform or normal distribution-it does not produce binned (discretized) output. The goal requires grouping values into bins to predict a target column…
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Options
- AYes
- BNo
How the community answered
(46 responses)- A24% (11)
- B76% (35)
Explanation
Quantiles normalization with QuantileIndex is a data normalization technique that rescales feature values so they follow a uniform or normal distribution-it does not produce binned (discretized) output. The goal requires grouping values into bins to predict a target column, which is a discretization/binning operation. For that purpose, the correct module in Azure ML Studio is 'Group Data into Bins' using modes such as Quantiles binning, Equal Width, Custom Edges, or MDL. Normalization and binning are distinct operations, so this solution does not meet the goal.
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