Arun Chhikara

Is there a way to transform a new data as per pipeline trained on a given task. For example:- ```r ames = mlr3data::ames_housing ames1 = ames[1:2000,] ames2 = ames[2001:nrow(ames),-c('Sale_Price')] to_remove...

resample$score(predict_sets = 'test') gives same output as resample$score(predict_sets = 'train'). Also, is there any functionality where results from both train and test can be accessed?

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### Description In both the situations, i think it just outputs test results ... ### Reproducible example tasks = tsks(c("german_credit", "sonar")) learners = lrns(c("classif.rpart", "classif.ranger","classif.featureless"), predict_type = "prob") rsmp_cv5 =...

Greetings mlr3 team, Would like to know if there is any functionality in mlr3 framework for calibrating the predicted probabilities through logistic regression or plat scaling or isotonic regression or...