get_varimp: Get variable importance
In rtemis: Schema-Driven Machine Learning and Visualization
get_varimp R Documentation
Get variable importance
Description
The variable importance measures a fitted model reports, or the mean
absolute contribution of each predictor in a SHAP explanation.
Usage
get_varimp(x, ...)
Arguments
x
Supervised, SupervisedRes or SHAP object.
...
Additional arguments passed to methods.
Details
A VariableImportance object holds its measures by name in @measures.
Each measure states what it quantifies (@kind, for example split gain,
permutation, or coefficient), the cases it was computed on
(@computed_on), whether its values can be negative (@signed) or depend
on the units of the predictors (@scale_dependent), how it ranks
predictors (@direction), and what its values are for this model
(@description); @values holds the value for each predictor.
varimp_table combines the measures into one data.frame.
Value
VariableImportance object, a list of them (one per resample) for
a SupervisedRes, or NULL when the algorithm reports no importance.
Author(s)
EDG
Examples
mod <- train(iris, hyperparameters = setup_LightRF())
get_varimp(mod)
rtemis documentation built on Oct. 20, 2026, 1:06 a.m.
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| get_varimp | R Documentation |
Get variable importance
Description
The variable importance measures a fitted model reports, or the mean
absolute contribution of each predictor in a SHAP explanation.
Usage
get_varimp(x, ...)
Arguments
x |
|
... |
Additional arguments passed to methods. |
Details
A VariableImportance object holds its measures by name in @measures.
Each measure states what it quantifies (@kind, for example split gain,
permutation, or coefficient), the cases it was computed on
(@computed_on), whether its values can be negative (@signed) or depend
on the units of the predictors (@scale_dependent), how it ranks
predictors (@direction), and what its values are for this model
(@description); @values holds the value for each predictor.
varimp_table combines the measures into one data.frame.
Value
VariableImportance object, a list of them (one per resample) for
a SupervisedRes, or NULL when the algorithm reports no importance.
Author(s)
EDG
Examples
mod <- train(iris, hyperparameters = setup_LightRF())
get_varimp(mod)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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