How should you configure the Clean Missing Data module?

HOTSPOT

You need to replace the missing data in the Accessibility To High way columns.

How should you configure the Clean Missing Data module? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

View Answer

Answer:

Explanation:

Box 1: Replace using MICE

Replace using MICE: For each missing value, this option assigns a new value, which is calculated by using a method described in the statistical literature as "Multivariate Imputation using Chained Equations" or "Multiple Imputation by Chained Equations". With a multiple imputation method, each variable with missing data is modeled conditionally using the other variables in the data before filling in the missing values.

Scenario: The Accessibility To High way column in both datasets contains missing values. The missing data must be replaced with new data so that it is modeled conditionally using the other variables in the data before filling in the missing values.

Box 2: Propagate

Cols with all missing values indicate if columns of all missing values should be preserved in the output.

References: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/clean-missing-data