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Questions tagged [mlr3]

mlr3 is the next generation of the mlr package for machine learning in R.

mlr3 is a redesigned version of the mlr package for machine learning in R, embracing R6 and data.table for cleaner code and more efficient operations. It provides a common interface to many learners that are implemented in R and many additional things, such as hyperparameter tuning and machine learning pipelines, on top. More information at https://mlr3.mlr-org.com/

mlr3 is a collection of packages with minimal dependencies between them to make installation easier. The mlr3 ecosystem comprises

  • the core package mlr3 and mlr3misc for miscellaneous additional functionality
  • mlr3featsel for feature selection
  • mlr3pipelines for machine learning pipelines
  • mlr3tuning for hyperparameter tuning
  • mlr3learners and mlr3extralearners for additional learner interfaces
  • mlr3ordinal for ordinal regression
  • mlr3survival for survival analysis
  • mlr3cluster for cluster analysis
  • mlr3forecasting for forecasting
  • mlr3fda for functional data analysis
  • mlr3spatiotemporal for spatial and temporal analytics
  • mlr3keras for deep learning with Keras
  • mlr3viz for visualizations
258 questions
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Apply Models from Nested Resample to Permuted Dataset

I have generated a nested resampling object with the following code: data<-read.csv("Data.csv", row.names=1) data$factor<-as.factor(data$factor) set.seed(123, "L'Ecuyer") task = as_task_classif(data, target = "factor") learner =…
abadgerw123
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Predict on holdout set using mlr3

I am using mlr3 package. I set roles of some rows to "holdout" and than trained the model: library(mlr3) # train on iris task = tsk("iris") task$nrow task$set_row_roles(130:150, "holdout") learner = lrn("classif.rpart") learner$train(task) How can…
Mislav Sagovac
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mlr3 standard deviation for k-fold cross-validation resampling

Anybody know how to extract the standard deviation for a ResampleResult/BenchmarkResult in mlr3? The implemented metrics seems to be returning only the average value. measures <- list( mlr3::msr("classif.fbeta", predict_sets = "train", id =…
Lucas Teixeira
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How do I tune random forest with oob error?

Instead of doing a CV and train the Random Forest multiple times I would like to use the OOB Error as and unbiased estimation of the generalized error. And for a few data points (in the low thousands), does it make sense to use the OOB error instead…
Seb
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get coefficients and features from a glmnet learner #mlr3

Thanks for providing the mlr3 package in R , since I am trying it for the first time simple code in mlr3: learner = lrn("classif.cv_glmnet") lrn_glmnet <- learner$train(task, row_ids = train_set). my question is how to get the features and…
Haneme
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How to obtain out of sample predictions on new data with mlr3 resample stored models?

I want to use mlr3 for cross-fitting of nuisance parameters in a semi-parametric model such as TMLE or AIPW. The cross-fitting procedure is similar to k-fold cross-validation; split the data into K sets of somewhat equal size, obtain predictions for…
N. Williams
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Imputation of target using mlr3

After studying the sources describing mlr3 and looking at the given examples I still couldn't find any answer about how to impute the target variable during a regression task, when it has missings. I want to use Ranger, but it can't deal with…
Nucore
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How to set the graph learner id in mlr3pipelines?

I construct a benchmark with 4 graph learners on 1 dataset. The learner_id of the result of the benchmark is so long because I have some preprocessings. How can I set the learner id so that it wouldn't too long. Here's my code: # step 1 the…
Yue Li
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How to set "budget" tag for xgboost hyperband optimization with mlr3tuningspaces?

I am trying to tune xgboost with hyperband and I would like to use the suggested default tuning space from the mlr3tuningspaces package. However, I don't find how to tag a hyperparameter with "budget" while using lts . Below, I reproduced the…
user2165907
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mlr3: extract variable importance for each resampling iteration

I would like to extract variable importance for each resampling iteration with mlr3. So far, I have only found a "manual" way of doing it so I was wondering if there was a wrapper function or some other way to do it. Below is a toy example with…
user2165907
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feature importance in mlr3 with iml for classification forests

I calculate feature importance for 2 different types of machine learning models (SVM and Classification Forest). I cannot post the data here, but I describe what I do: My (classification) task has about 400 observations of 70 variables. Some of them…
ds_col
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I need good model serialization. Default R serialization is nighter safe nor effective from the point of model size

MLR3 model includes a lot of redundant data not needed when applying the model. The traditional R approach is to save all the data used for model training. It leads to the growth of used memory. What leads to the growth of used memory. In the…
Taras Hishchak
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mlr3 survival distribution estimation at specific time-points

I'm looking for a faster way to extract predicted survival distributions with mlr3 and mlr3proba. The prediction procedure is highly time-consuming, expecially using datasets with hundreds of observations and without ties in time variable. Does it…
GabrieleInfante
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How to perform spatial crossvalidation using mlr3 and then perform raster predict

I have the following problem. I want to build a model for landcover classification. My data are multitemporal Remote Sensing data with several bands. For training I created stratified randomly distributed points to extract spectral data at their…
nvnor
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How to combine autofselector and autotuner models in a Benchmark

How I can make a list of learners including autofselector and autotuner in benchmark and compare their performance? I wonder how to rank learners stratified by task when we have multiple tasks library(mlr3verse) mod1 = AutoTuner$new( …
Ali Alhadab
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