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mlr (version 2.10)

getFeatureImportanceLearner.regr.randomForestSRC: Calculates feature importance values for a given learner.

Description

This function is mostly for internal usage. To calculate feature importance use getFeatureImportance. The return value is a named numeric vector. There does not need to be one value for each feature in the dataset. In getFeatureImportance missing features will get an importance of zero and if the vector contains NA they will also be replaced with zero.

Usage

# S3 method for regr.randomForestSRC
getFeatureImportanceLearner(.learner, .model,
  ...)
getFeatureImportanceLearner(.learner, .model, ...)

Arguments

.learner
[Learner | character(1)] The learner.
.model
[WrappedModel] The model.
...
[any] Additional parameters, which are passed to the underlying importance value generating function.

Value

[numeric] A named vector of variable importance.