datarobot (version 2.8.0)

GetFeatureImpactForModel: Retrieve completed Feature Impact results given a model

Description

This will only succeed if the Feature Impact computation has completed.

Usage

GetFeatureImpactForModel(model)

Arguments

model

character. The model for which you want to retrieve Feature Impact.

Value

A data frame with the following columns:

featureName

The name of the feature

impactNormalized

The normalized impact score (largest value is 1)

impactUnnormalized

The unnormalized impact score

Details

Feature Impact is computed for each column by creating new data with that column randomly permuted (but the others left unchanged), and seeing how the error metric score for the predictions is affected. The 'impactUnnormalized' is how much worse the error metric score is when making predictions on this modified data. The 'impactNormalized' is normalized so that the largest value is 1. In both cases, larger values indicate more important features. Elsewhere this technique is sometimes called 'Permutation Importance'.

Examples

# NOT RUN {
  model <- ListModels(project)[[1]]
  featureImpactJobId <- RequestFeatureImpact(model)
  # Note: This will only work after the feature impact job has completed. Use
  #       GetFeatureImpactFromIobId to automatically wait for the job.\
  featureImpact <- GetFeatureImpactForModel(model)
# }