Appendix D — Overview Tables

Our homepage provides overviews and tables of the following objects:

Description	Link
Packages overview	https://mlr-org.com/packages.html
Task overview	https://mlr-org.com/tasks.html
Learner overview	https://mlr-org.com/learners.html
Resampling overview	https://mlr-org.com/resamplings.html
Measure overview	https://mlr-org.com/measures.html
PipeOp overview	https://mlr-org.com/pipeops.html
Graph overview	https://mlr-org.com/graphs.html
Tuner overview	https://mlr-org.com/tuners.html
Terminator overview	https://mlr-org.com/terminators.html
Tuning space overview	https://mlr-org.com/tuning_spaces.html
Filter overview	https://mlr-org.com/filters.html
FSelector overview	https://mlr-org.com/fselectors.html

library(mlr3verse)
library(mlr3proba)
library(mlr3spatiotempcv)
library(mlr3spatial)
library(mlr3extralearners)
library(mlr3hyperband)
library(mlr3mbo)

mlr_tasks

<DictionaryTask> with 33 stored values
Keys: actg, bike_sharing, boston_housing, breast_cancer, cookfarm_mlr3,
  diplodia, ecuador, faithful, gbcs, german_credit, grace, ilpd, iris,
  kc_housing, leipzig, lung, moneyball, mtcars, optdigits, penguins,
  penguins_simple, pima, precip, rats, ruspini, sonar, spam, titanic,
  unemployment, usarrests, whas, wine, zoo

mlr_learners

<DictionaryLearner> with 145 stored values
Keys: classif.abess, classif.AdaBoostM1, classif.bart, classif.C50,
  classif.catboost, classif.cforest, classif.ctree, classif.cv_glmnet,
  classif.debug, classif.earth, classif.featureless, classif.fnn,
  classif.gam, classif.gamboost, classif.gausspr, classif.gbm,
  classif.glmboost, classif.glmer, classif.glmnet, classif.IBk,
  classif.imbalanced_rfsrc, classif.J48, classif.JRip, classif.kknn,
  classif.ksvm, classif.lda, classif.liblinear, classif.lightgbm,
  classif.LMT, classif.log_reg, classif.lssvm, classif.mob,
  classif.multinom, classif.naive_bayes, classif.nnet, classif.OneR,
  classif.PART, classif.priority_lasso, classif.qda,
  classif.randomForest, classif.ranger, classif.rfsrc, classif.rpart,
  classif.svm, classif.xgboost, clust.agnes, clust.ap, clust.cmeans,
  clust.cobweb, clust.dbscan, clust.diana, clust.em, clust.fanny,
  clust.featureless, clust.ff, clust.hclust, clust.kkmeans,
  clust.kmeans, clust.MBatchKMeans, clust.mclust, clust.meanshift,
  clust.pam, clust.SimpleKMeans, clust.xmeans, dens.hist, dens.kde,
  dens.kde_ks, dens.locfit, dens.logspline, dens.mixed, dens.nonpar,
  dens.pen, dens.plug, dens.spline, regr.abess, regr.bart,
  regr.catboost, regr.cforest, regr.ctree, regr.cubist, regr.cv_glmnet,
  regr.debug, regr.earth, regr.featureless, regr.fnn, regr.gam,
  regr.gamboost, regr.gausspr, regr.gbm, regr.glm, regr.glmboost,
  regr.glmnet, regr.IBk, regr.kknn, regr.km, regr.ksvm, regr.liblinear,
  regr.lightgbm, regr.lm, regr.lmer, regr.M5Rules, regr.mars, regr.mob,
  regr.nnet, regr.priority_lasso, regr.randomForest, regr.ranger,
  regr.rfsrc, regr.rpart, regr.rsm, regr.rvm, regr.svm, regr.xgboost,
  surv.akritas, surv.aorsf, surv.blackboost, surv.cforest,
  surv.coxboost, surv.coxph, surv.coxtime, surv.ctree,
  surv.cv_coxboost, surv.cv_glmnet, surv.deephit, surv.deepsurv,
  surv.dnnsurv, surv.flexible, surv.gamboost, surv.gbm, surv.glmboost,
  surv.glmnet, surv.kaplan, surv.loghaz, surv.mboost, surv.nelson,
  surv.obliqueRSF, surv.parametric, surv.pchazard, surv.penalized,
  surv.priority_lasso, surv.ranger, surv.rfsrc, surv.rpart, surv.svm,
  surv.xgboost

mlr_resamplings

<DictionaryResampling> with 24 stored values
Keys: bootstrap, custom, custom_cv, cv, holdout, insample, loo,
  repeated_cv, repeated_spcv_block, repeated_spcv_coords,
  repeated_spcv_disc, repeated_spcv_env, repeated_spcv_tiles,
  repeated_sptcv_cluto, repeated_sptcv_cstf, spcv_block, spcv_buffer,
  spcv_coords, spcv_disc, spcv_env, spcv_tiles, sptcv_cluto,
  sptcv_cstf, subsampling

mlr_measures

<DictionaryMeasure> with 92 stored values
Keys: aic, bic, classif.acc, classif.auc, classif.bacc, classif.bbrier,
  classif.ce, classif.costs, classif.dor, classif.fbeta, classif.fdr,
  classif.fn, classif.fnr, classif.fomr, classif.fp, classif.fpr,
  classif.logloss, classif.mauc_au1p, classif.mauc_au1u,
  classif.mauc_aunp, classif.mauc_aunu, classif.mbrier, classif.mcc,
  classif.npv, classif.ppv, classif.prauc, classif.precision,
  classif.recall, classif.sensitivity, classif.specificity, classif.tn,
  classif.tnr, classif.tp, classif.tpr, clust.ch, clust.dunn,
  clust.silhouette, clust.wss, debug_classif, dens.logloss, oob_error,
  regr.bias, regr.ktau, regr.logloss, regr.mae, regr.mape, regr.maxae,
  regr.medae, regr.medse, regr.mse, regr.msle, regr.pbias, regr.rae,
  regr.rmse, regr.rmsle, regr.rrse, regr.rse, regr.rsq, regr.sae,
  regr.smape, regr.srho, regr.sse, selected_features, sim.jaccard,
  sim.phi, surv.brier, surv.calib_alpha, surv.calib_beta,
  surv.chambless_auc, surv.cindex, surv.dcalib, surv.graf,
  surv.hung_auc, surv.intlogloss, surv.logloss, surv.mae, surv.mse,
  surv.nagelk_r2, surv.oquigley_r2, surv.rcll, surv.rmse, surv.schmid,
  surv.song_auc, surv.song_tnr, surv.song_tpr, surv.uno_auc,
  surv.uno_tnr, surv.uno_tpr, surv.xu_r2, time_both, time_predict,
  time_train

mlr_pipeops

<DictionaryPipeOp> with 74 stored values
Keys: boxcox, branch, chunk, classbalancing, classifavg, classweights,
  colapply, collapsefactors, colroles, compose_crank, compose_distr,
  compose_probregr, copy, crankcompose, datefeatures, distrcompose,
  encode, encodeimpact, encodelmer, featureunion, filter, fixfactors,
  histbin, ica, imputeconstant, imputehist, imputelearner, imputemean,
  imputemedian, imputemode, imputeoor, imputesample, kernelpca,
  learner, learner_cv, missind, modelmatrix, multiplicityexply,
  multiplicityimply, mutate, nmf, nop, ovrsplit, ovrunite, pca, proxy,
  quantilebin, randomprojection, randomresponse, regravg,
  removeconstants, renamecolumns, replicate, scale, scalemaxabs,
  scalerange, select, smote, spatialsign, subsample, survavg,
  targetinvert, targetmutate, targettrafoscalerange, textvectorizer,
  threshold, trafopred_regrsurv, trafopred_survregr,
  trafotask_regrsurv, trafotask_survregr, tunethreshold, unbranch,
  vtreat, yeojohnson

mlr_graphs

<DictionaryGraph> with 13 stored values
Keys: bagging, branch, crankcompositor, distrcompositor, greplicate,
  ovr, probregr, robustify, stacking, survaverager, survbagging,
  survtoregr, targettrafo

mlr_tuners

<DictionaryTuner> with 10 stored values
Keys: cmaes, design_points, gensa, grid_search, hyperband, irace, mbo,
  nloptr, random_search, successive_halving

mlr_terminators

<DictionaryTerminator> with 8 stored values
Keys: clock_time, combo, evals, none, perf_reached, run_time,
  stagnation, stagnation_batch

mlr_tuning_spaces

<DictionaryTuningSpaces> with 24 stored values
Keys: classif.glmnet.default, classif.glmnet.rbv2,
  classif.kknn.default, classif.kknn.rbv2, classif.ranger.default,
  classif.ranger.rbv2, classif.rpart.default, classif.rpart.rbv2,
  classif.svm.default, classif.svm.rbv2, classif.xgboost.default,
  classif.xgboost.rbv2, regr.glmnet.default, regr.glmnet.rbv2,
  regr.kknn.default, regr.kknn.rbv2, regr.ranger.default,
  regr.ranger.rbv2, regr.rpart.default, regr.rpart.rbv2,
  regr.svm.default, regr.svm.rbv2, regr.xgboost.default,
  regr.xgboost.rbv2

mlr_filters

<DictionaryFilter> with 21 stored values
Keys: anova, auc, carscore, carsurvscore, cmim, correlation, disr,
  find_correlation, importance, information_gain, jmi, jmim,
  kruskal_test, mim, mrmr, njmim, performance, permutation, relief,
  selected_features, variance

mlr_fselectors

<DictionaryFSelector> with 8 stored values
Keys: design_points, exhaustive_search, genetic_search, random_search,
  rfe, rfecv, sequential, shadow_variable_search