mlr3.model_extractor: Model Extractor Callback

In mlr3: Machine Learning in R - Next Generation

Model Extractor Callback

Description

This CallbackResample extracts information from the model after training with a user-defined function. This way information can be extracted from the model without saving the model (store_models = FALSE). The fun must be a function that takes a learner as input and returns the extracted information as named list (see example). The callback is very helpful to call ⁠$selected_features()⁠, ⁠$importance()⁠, ⁠$oob_error()⁠ on the learner.

Arguments

fun	(⁠function(learner)⁠) Function to extract information from the learner. The function must have the argument learner. The function must return a named list.

Examples

task = tsk("pima")
learner = lrn("classif.rpart")
resampling = rsmp("cv", folds = 3)

# define function to extract selected features
selected_features = function(learner) list(selected_features = learner$selected_features())

# create callback
callback = clbk("mlr3.model_extractor", fun = selected_features)

rr = resample(task, learner, resampling = resampling, store_models = FALSE, callbacks = callback)

rr$data_extra

mlr3 documentation built on April 4, 2025, 5:08 a.m.