Add a sample for Permutation Feature Importance #1728
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Co-Authored-By: rogancarr <[email protected]>
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| var weights = GetLinearModelWeights(linearPredictor.Model); | ||
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| // Compute the permutation metrics using the properly-featurized data. | ||
| var transformedData = fitPipeline.Transform(data); |
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It implies that feature name can't not be identical to predicted label/score name produced by the linear model. Could you make a note here?
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The PFI calculation actually does its own scoring, and should do this. I actually just do this to produce the Features column.
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This PR adds a sample for using
PermutationFeatureImportance.The sample looks at the feature importances for a linear model predicting housing prices with the
HousingRegressiondataset and shows how to interpret the output ofPermutationFeatureImportanceas a measure of global feature importance.Fixes #1723