mlr3 (version 0.23.0)

mlr3.model_extractor: 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