Package: mlr3 0.20.0
Marc Becker
mlr3:Machine Learning in R - Next Generation
Efficient, object-oriented programming on the building blocks of machine learning. Provides 'R6' objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While 'mlr3' focuses on the core computational operations, add-on packages provide additional functionality.
Authors:
mlr3_0.20.0.tar.gz
mlr3_0.20.0.tar.gz(r-4.5-noble)mlr3_0.20.0.tar.gz(r-4.4-noble)
mlr3_0.20.0.tgz(r-4.4-emscripten)mlr3_0.20.0.tgz(r-4.3-emscripten)
mlr3.pdf |mlr3.html✨
mlr3/json (API)
NEWS
| # Installmlr3 in R: |
| install.packages('mlr3',repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mlr-org/mlr3/issues
Last updated 7 days agofrom:7029492ae6
Exports:as_benchmark_resultas_data_backendas_learneras_learnersas_measureas_measuresas_predictionas_prediction_classifas_prediction_dataas_prediction_regras_predictionsas_resample_resultas_resamplingas_resamplingsas_result_dataas_taskas_task_classifas_task_regras_task_unsupervisedas_tasksas_tasks_unsupervisedas.data.tableassert_backendassert_benchmark_resultassert_learnableassert_learnerassert_learnersassert_measureassert_measuresassert_predictableassert_predictionassert_resample_resultassert_resamplingassert_resamplingsassert_row_idsassert_taskassert_tasksassert_validateauto_convertbenchmarkbenchmark_gridBenchmarkResultcheck_prediction_datacol_infoconvert_taskdata.tableDataBackendDataBackendDataTableDataBackendMatrixdefault_measuresextract_pkgsfilter_prediction_dataHotstartStackinstall_pkgsis_marshaled_modelis_missing_prediction_dataLearnerlearner_marshallearner_marshaledlearner_unmarshalLearnerClassifLearnerClassifDebugLearnerClassifFeaturelessLearnerClassifRpartLearnerRegrLearnerRegrDebugLearnerRegrFeaturelessLearnerRegrRpartlrnlrnsmarshal_modelMeasureMeasureAICMeasureBICMeasureClassifMeasureClassifCostsMeasureDebugClassifMeasureElapsedTimeMeasureInternalValidScoreMeasureOOBErrorMeasureRegrMeasureSelectedFeaturesMeasureSimilaritymlr_learnersmlr_measuresmlr_reflectionsmlr_resamplingsmlr_task_generatorsmlr_tasksmsrmsrspartitionPredictionPredictionClassifPredictionRegrresampleResampleResultResamplingResamplingBootstrapResamplingCustomResamplingCustomCVResamplingCVResamplingHoldoutResamplingInsampleResamplingLOOResamplingRepeatedCVResamplingSubsamplingResultDatarsmprsmpsset_threadsset_validateTaskTaskClassifTaskGeneratorTaskGenerator2DNormalsTaskGeneratorCassiniTaskGeneratorCircleTaskGeneratorFriedman1TaskGeneratorMoonsTaskGeneratorSimplexTaskGeneratorSmileyTaskGeneratorSpiralsTaskGeneratorXorTaskRegrTaskSupervisedTaskUnsupervisedtgentgenstsktsksunmarshal_model
Dependencies:backportscheckmatecodetoolsdata.tabledigestevaluatefuturefuture.applyglobalslgrlistenvmlbenchmlr3measuresmlr3miscpalmerpenguinsparadoxparallellyPRROCR6RhpcBLASctluuid
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| mlr3: Machine Learning in R - Next Generation | mlr3-package mlr3 |
| Convert to BenchmarkResult | as_benchmark_result as_benchmark_result.BenchmarkResult as_benchmark_result.ResampleResult |
| Create a Data Backend | as_data_backend as_data_backend.data.frame as_data_backend.Matrix |
| Convert to a Learner | as_learner as_learner.Learner as_learners as_learners.default as_learners.list |
| Convert to a Measure | as_measure as_measure.Measure as_measure.NULL as_measures as_measures.default as_measures.list as_measures.NULL |
| Convert to a Prediction | as_prediction as_prediction.Prediction as_prediction.PredictionDataClassif as_prediction.PredictionDataRegr as_predictions as_predictions.list |
| Convert to a Classification Prediction | as_prediction_classif as_prediction_classif.data.frame as_prediction_classif.PredictionClassif |
| PredictionData | as_prediction_data as_prediction_data.list as_prediction_data.Prediction as_prediction_data.PredictionData |
| Convert to a Regression Prediction | as_prediction_regr as_prediction_regr.data.frame as_prediction_regr.PredictionRegr |
| Convert to ResampleResult | as_resample_result as_resample_result.list as_resample_result.ResampleResult as_resample_result.ResultData |
| Convert to a Resampling | as_resampling as_resampling.Resampling as_resamplings as_resamplings.default as_resamplings.list |
| Convert to ResultData | as_result_data |
| Convert to a Task | as_task as_task.Task as_tasks as_tasks.default as_tasks.list |
| Convert to a Classification Task | as_task_classif as_task_classif.data.frame as_task_classif.DataBackend as_task_classif.formula as_task_classif.Matrix as_task_classif.matrix as_task_classif.TaskClassif as_task_classif.TaskRegr |
| Convert to a Regression Task | as_task_regr as_task_regr.data.frame as_task_regr.DataBackend as_task_regr.formula as_task_regr.Matrix as_task_regr.matrix as_task_regr.TaskClassif as_task_regr.TaskRegr |
| Convert to an Unsupervised Task | as_tasks_unsupervised as_tasks_unsupervised.list as_tasks_unsupervised.Task as_task_unsupervised as_task_unsupervised.data.frame as_task_unsupervised.DataBackend as_task_unsupervised.Task |
| Benchmark Multiple Learners on Multiple Tasks | benchmark |
| Generate a Benchmark Grid Design | benchmark_grid |
| Container for Benchmarking Results | BenchmarkResult |
| Convert a Task from One Type to Another | convert_task |
| DataBackend | DataBackend |
| DataBackend for data.table | DataBackendDataTable |
| DataBackend for Matrix | DataBackendMatrix |
| Get the Default Measure | default_measures |
| Stack for Hot Start Learners | HotstartStack |
| Install (Missing) Packages | extract_pkgs extract_pkgs.BenchmarkResult extract_pkgs.character extract_pkgs.list extract_pkgs.R6 extract_pkgs.ResampleResult install_pkgs |
| Learner Class | Learner |
| Classification Learner | LearnerClassif |
| Regression Learner | LearnerRegr |
| Measure Class | Measure |
| Classification Measure | MeasureClassif |
| Regression Measure | MeasureRegr |
| Similarity Measure | MeasureSimilarity |
| Dictionary of Learners | mlr_learners |
| Classification Learner for Debugging | LearnerClassifDebug mlr_learners_classif.debug |
| Featureless Classification Learner | LearnerClassifFeatureless mlr_learners_classif.featureless |
| Classification Tree Learner | LearnerClassifRpart mlr_learners_classif.rpart |
| Regression Learner for Debugging | LearnerRegrDebug mlr_learners_regr.debug |
| Featureless Regression Learner | LearnerRegrFeatureless mlr_learners_regr.featureless |
| Regression Tree Learner | LearnerRegrRpart mlr_learners_regr.rpart |
| Dictionary of Performance Measures | mlr_measures |
| Akaike Information Criterion Measure | MeasureAIC mlr_measures_aic |
| Bayesian Information Criterion Measure | MeasureBIC mlr_measures_bic |
| Classification Accuracy | mlr_measures_classif.acc |
| Area Under the ROC Curve | mlr_measures_classif.auc |
| Balanced Accuracy | mlr_measures_classif.bacc |
| Binary Brier Score | mlr_measures_classif.bbrier |
| Classification Error | mlr_measures_classif.ce |
| Cost-sensitive Classification Measure | MeasureClassifCosts mlr_measures_classif.costs |
| Diagnostic Odds Ratio | mlr_measures_classif.dor |
| F-beta Score | mlr_measures_classif.fbeta |
| False Discovery Rate | mlr_measures_classif.fdr |
| False Negatives | mlr_measures_classif.fn |
| False Negative Rate | mlr_measures_classif.fnr |
| False Omission Rate | mlr_measures_classif.fomr |
| False Positives | mlr_measures_classif.fp |
| False Positive Rate | mlr_measures_classif.fpr |
| Log Loss | mlr_measures_classif.logloss |
| Multiclass AUC Scores | mlr_measures_classif.mauc_au1p |
| Multiclass AUC Scores | mlr_measures_classif.mauc_au1u |
| Multiclass AUC Scores | mlr_measures_classif.mauc_aunp |
| Multiclass AUC Scores | mlr_measures_classif.mauc_aunu |
| Multiclass Brier Score | mlr_measures_classif.mbrier |
| Matthews Correlation Coefficient | mlr_measures_classif.mcc |
| Negative Predictive Value | mlr_measures_classif.npv |
| Positive Predictive Value | mlr_measures_classif.ppv |
| Area Under the Precision-Recall Curve | mlr_measures_classif.prauc |
| Positive Predictive Value | mlr_measures_classif.precision |
| True Positive Rate | mlr_measures_classif.recall |
| True Positive Rate | mlr_measures_classif.sensitivity |
| True Negative Rate | mlr_measures_classif.specificity |
| True Negatives | mlr_measures_classif.tn |
| True Negative Rate | mlr_measures_classif.tnr |
| True Positives | mlr_measures_classif.tp |
| True Positive Rate | mlr_measures_classif.tpr |
| Debug Measure for Classification | MeasureDebugClassif mlr_measures_debug_classif |
| Elapsed Time Measure | MeasureElapsedTime mlr_measures_elapsed_time mlr_measures_time_both mlr_measures_time_predict mlr_measures_time_train |
| Measure Internal Validation Score | MeasureInternalValidScore mlr_measures_internal_valid_score |
| Out-of-bag Error Measure | MeasureOOBError mlr_measures_oob_error |
| Bias | mlr_measures_regr.bias |
| Kendall's tau | mlr_measures_regr.ktau |
| Mean Absolute Error | mlr_measures_regr.mae |
| Mean Absolute Percent Error | mlr_measures_regr.mape |
| Max Absolute Error | mlr_measures_regr.maxae |
| Median Absolute Error | mlr_measures_regr.medae |
| Median Squared Error | mlr_measures_regr.medse |
| Mean Squared Error | mlr_measures_regr.mse |
| Mean Squared Log Error | mlr_measures_regr.msle |
| Percent Bias | mlr_measures_regr.pbias |
| Relative Absolute Error | mlr_measures_regr.rae |
| Root Mean Squared Error | mlr_measures_regr.rmse |
| Root Mean Squared Log Error | mlr_measures_regr.rmsle |
| Root Relative Squared Error | mlr_measures_regr.rrse |
| Relative Squared Error | mlr_measures_regr.rse |
| R Squared | mlr_measures_regr.rsq |
| Sum of Absolute Errors | mlr_measures_regr.sae |
| Symmetric Mean Absolute Percent Error | mlr_measures_regr.smape |
| Spearman's rho | mlr_measures_regr.srho |
| Sum of Squared Errors | mlr_measures_regr.sse |
| Selected Features Measure | MeasureSelectedFeatures mlr_measures_selected_features |
| Jaccard Similarity Index | mlr_measures_sim.jaccard |
| Phi Coefficient Similarity | mlr_measures_sim.phi |
| Dictionary of Resampling Strategies | mlr_resamplings |
| Bootstrap Resampling | mlr_resamplings_bootstrap ResamplingBootstrap |
| Custom Resampling | mlr_resamplings_custom ResamplingCustom |
| Custom Cross-Validation | mlr_resamplings_custom_cv ResamplingCustomCV |
| Cross-Validation Resampling | mlr_resamplings_cv ResamplingCV |
| Holdout Resampling | mlr_resamplings_holdout ResamplingHoldout |
| Insample Resampling | mlr_resamplings_insample ResamplingInsample |
| Leave-One-Out Cross-Validation | mlr_resamplings_loo ResamplingLOO |
| Repeated Cross-Validation Resampling | mlr_resamplings_repeated_cv ResamplingRepeatedCV |
| Subsampling Resampling | mlr_resamplings_subsampling ResamplingSubsampling |
| Syntactic Sugar for Object Construction | lrn lrns mlr_sugar msr msrs rsmp rsmps set_validate tgen tgens tsk tsks |
| Dictionary of Task Generators | mlr_task_generators |
| 2D Normals Classification Task Generator | mlr_task_generators_2dnormals TaskGenerator2DNormals |
| Cassini Classification Task Generator | mlr_task_generators_cassini TaskGeneratorCassini |
| Circle Classification Task Generator | mlr_task_generators_circle TaskGeneratorCircle |
| Friedman1 Regression Task Generator | mlr_task_generators_friedman1 TaskGeneratorFriedman1 |
| Moons Classification Task Generator | mlr_task_generators_moons TaskGeneratorMoons |
| Simplex Classification Task Generator | mlr_task_generators_simplex TaskGeneratorSimplex |
| Smiley Classification Task Generator | mlr_task_generators_smiley TaskGeneratorSmiley |
| Spiral Classification Task Generator | mlr_task_generators_spirals TaskGeneratorSpirals |
| XOR Classification Task Generator | mlr_task_generators_xor TaskGeneratorXor |
| Dictionary of Tasks | mlr_tasks |
| Boston Housing Regression Task | mlr_tasks_boston_housing |
| Wisconsin Breast Cancer Classification Task | mlr_tasks_breast_cancer |
| German Credit Classification Task | mlr_tasks_german_credit |
| Iris Classification Task | mlr_tasks_iris |
| Motor Trend Regression Task | mlr_tasks_mtcars |
| Palmer Penguins Data Set | mlr_tasks_penguins |
| Pima Indian Diabetes Classification Task | mlr_tasks_pima |
| Sonar Classification Task | mlr_tasks_sonar |
| Spam Classification Task | mlr_tasks_spam |
| Wine Classification Task | mlr_tasks_wine |
| Zoo Classification Task | mlr_tasks_zoo |
| Documentation of mlr3 test helpers | mlr_test_helpers |
| Manually Partition into Training and Test Set | partition partition.TaskClassif partition.TaskRegr |
| Predict Method for Learners | predict.Learner |
| Abstract Prediction Object | Prediction |
| Prediction Object for Classification | PredictionClassif |
| Convert to PredictionData | c.PredictionDataClassif c.PredictionDataRegr check_prediction_data check_prediction_data.PredictionDataClassif check_prediction_data.PredictionDataRegr filter_prediction_data is_missing_prediction_data is_missing_prediction_data.PredictionDataClassif is_missing_prediction_data.PredictionDataRegr PredictionData |
| Prediction Object for Regression | PredictionRegr |
| Resample a Learner on a Task | resample |
| Container for Results of 'resample()' | ResampleResult |
| Resampling Class | Resampling |
| Set the Number of Threads | set_threads set_threads.default set_threads.list set_threads.R6 |
| Task Class | Task |
| Classification Task | TaskClassif |
| TaskGenerator Class | TaskGenerator |
| Regression Task | TaskRegr |
