Function reference • mlr3

Building Blocks
`Task`	Task Class
`Learner`	Learner Class
`Measure`	Measure Class
`Resampling`	Resampling Class
`Prediction`	Abstract Prediction Object
Data Backends
`DataBackend`	DataBackend
`DataBackendDataTable`	DataBackend for data.table
`DataBackendMatrix`	DataBackend for Matrix
`as_data_backend()`	Create a Data Backend
Classification
`TaskClassif`	Classification Task
`LearnerClassif`	Classification Learner
`MeasureClassif`	Classification Measure
`PredictionClassif`	Prediction Object for Classification
Regression
`TaskRegr`	Regression Task
`LearnerRegr`	Regression Learner
`MeasureRegr`	Regression Measure
`PredictionRegr`	Prediction Object for Regression
Tasks
`mlr_tasks`	Dictionary of Tasks
`mlr_tasks_boston_housing`	Boston Housing Regression Task
`mlr_tasks_german_credit`	German Credit Classification Task
`mlr_tasks_iris`	Iris Classification Task
`mlr_tasks_mtcars`	Motor Trend Regression Task
`mlr_tasks_pima`	Pima Indian Diabetes Classification Task
`mlr_tasks_sonar`	Sonar Classification Task
`mlr_tasks_spam`	Spam Classification Task
`mlr_tasks_wine`	Wine Classification Task
`mlr_tasks_zoo`	Zoo Classification Task
Task Generators
`TaskGenerator`	TaskGenerator Class
`mlr_task_generators`	Dictionary of Task Generators
`mlr_task_generators_2dnormals`	2D Normals Classification Task Generator
`mlr_task_generators_friedman1`	Friedman1 Regression Task Generator
`mlr_task_generators_smiley`	Smiley Classification Task Generator
`mlr_task_generators_xor`	XOR Classification Task Generator
Learners
`mlr_learners`	Dictionary of Learners
`mlr_learners_classif.debug`	Classification Learner for Debugging
`mlr_learners_classif.featureless`	Featureless Classification Learner
`mlr_learners_classif.rpart`	Classification Tree Learner
`mlr_learners_regr.featureless`	Featureless Regression Learner
`mlr_learners_regr.rpart`	Regression Tree Learner
Measures
`mlr_measures`	Dictionary of Performance Measures
`mlr_measures_classif.acc`	Classification Accuracy
`mlr_measures_classif.auc`	Area Under the ROC Curve
`mlr_measures_classif.bacc`	Balanced Accuracy
`mlr_measures_classif.ce`	Classification Error
`mlr_measures_classif.costs`	Cost-sensitive Classification Measure
`mlr_measures_classif.dor`	Diagnostic Odds Ratio
`mlr_measures_classif.fbeta`	F-beta Score
`mlr_measures_classif.fdr`	False Discovery Rate
`mlr_measures_classif.fn`	False Negatives
`mlr_measures_classif.fnr`	False Negative Rate
`mlr_measures_classif.fomr`	False Omission Rate
`mlr_measures_classif.fp`	False Positives
`mlr_measures_classif.fpr`	False Positive Rate
`mlr_measures_classif.logloss`	Log Loss
`mlr_measures_classif.mcc`	Matthews Correlation Coefficient
`mlr_measures_classif.npv`	Negative Predictive Value
`mlr_measures_classif.ppv`	Positive Predictive Value
`mlr_measures_classif.precision`	Positive Predictive Value
`mlr_measures_classif.recall`	True Positive Rate
`mlr_measures_classif.sensitivity`	True Positive Rate
`mlr_measures_classif.specificity`	True Negative Rate
`mlr_measures_classif.tn`	True Negatives
`mlr_measures_classif.tnr`	True Negative Rate
`mlr_measures_classif.tp`	True Positives
`mlr_measures_classif.tpr`	True Positive Rate
`mlr_measures_debug`	Debug Measure
`mlr_measures_elapsed_time`	Elapsed Time Measure
`mlr_measures_oob_error`	Out-of-bag Error Measure
`mlr_measures_regr.bias`	Bias
`mlr_measures_regr.ktau`	Kendall's tau
`mlr_measures_regr.mae`	Mean Absolute Errors
`mlr_measures_regr.mape`	Mean Absolute Percent Error
`mlr_measures_regr.maxae`	Max Absolute Error
`mlr_measures_regr.medae`	Median Absolute Errors
`mlr_measures_regr.medse`	Median Squared Error
`mlr_measures_regr.mse`	Mean Squared Error
`mlr_measures_regr.msle`	Mean Squared Log Error
`mlr_measures_regr.pbias`	Percent Bias
`mlr_measures_regr.rae`	Relative Absolute Error
`mlr_measures_regr.rmse`	Root Mean Squared Error
`mlr_measures_regr.rmsle`	Root Mean Squared Log Error
`mlr_measures_regr.rrse`	Root Relative Squared Error
`mlr_measures_regr.rse`	Relative Squared Error
`mlr_measures_regr.rsq`	R Squared
`mlr_measures_regr.sae`	Sum of Absolute Errors
`mlr_measures_regr.smape`	Symmetric Mean Absolute Percent Error
`mlr_measures_regr.srho`	Spearman's rho
`mlr_measures_regr.sse`	Sum of Squared Errors
`mlr_measures_selected_features`	Selected Features Measure
`default_measures()`	Get a Default Measure
Resampling Strategies
`mlr_resamplings`	Dictionary of Resampling Strategies
`mlr_resamplings_bootstrap`	Bootstrap Resampling
`mlr_resamplings_custom`	Custom Resampling
`mlr_resamplings_cv`	Cross Validation Resampling
`mlr_resamplings_holdout`	Holdout Resampling
`mlr_resamplings_repeated_cv`	Repeated Cross Validation Resampling
`mlr_resamplings_subsampling`	Subsampling Resampling
Resample
`resample()`	Resample a Learner on a Task
`ResampleResult`	Container for Results of `resample()`
Benchmarking
`benchmark()`	Benchmark Multiple Learners on Multiple Tasks
`benchmark_grid()`	Generate a Benchmark Grid Design
`BenchmarkResult`	Container for Benchmarking Results
`as_benchmark_result()`	Convert to BenchmarkResult
Extending mlr3
`assert_backend()` `assert_task()` `assert_tasks()` `assert_learner()` `assert_learners()` `assert_learnable()` `assert_measure()` `assert_measures()` `assert_resampling()` `assert_resamplings()` `assert_prediction()` `assert_resample_result()` `assert_benchmark_result()` `assert_row_ids()`	Assertion for mlr3 Objects
`as_task()` `as_tasks()` `as_learner()` `as_learners()` `as_resampling()` `as_resamplings()` `as_measure()` `as_measures()`	Object Coercion
`mlr_reflections`	Reflections for mlr3
`tsk()` `tsks()` `tgen()` `tgens()` `lrn()` `lrns()` `rsmp()` `rsmps()` `msr()` `msrs()`	Syntactic Sugar for Object Construction
`predict(<Learner>)`	Predict Method for Learners

Reference

Building Blocks

Data Backends

Classification

Regression

Tasks

Task Generators

Learners

Measures

Resampling Strategies

Resample

Benchmarking

Extending mlr3

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