How Well Do You Understand ALE

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ICE plots visualize the dependence of the prediction on a feature for each instance separately
ICE plots create variants of an instance by replacing the feature's value with values from a grid
ICE plots show one line per instance compared to one line overall in PDPs (correct)
PDPs are the average of the lines of an ICE plot

<p>To visualize the dependence of the prediction on a feature for each instance separately (C)</p> Signup and view all the answers

<p>By replacing the feature's value with values from a grid to create variants of an instance (B)</p> Signup and view all the answers

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ALE is used to calculate the effect of a feature on the prediction.
The feature is divided into intervals and the difference in prediction is calculated for each interval.
The differences are accumulated and centered to create the ALE curve.
ALE can be interpreted as the main effect of the feature compared to the average prediction.
ALE correctly identifies linear relationships between features and prediction.
ICE plots visualize the dependence of the prediction on a feature for each instance separately.
ICE plots show one line per instance compared to one line overall in PDPs.
PDPs are the average of the lines of an ICE plot.
ICE plots create variants of an instance by replacing the feature's value with values from a grid.
ICE plots make predictions with the black box model for the newly created instances.