Sat, 13 Feb 2016

New package TransP with initial version 0.1
Package: TransP
Type: Package
Title: Implementation of Transportation Problem Algorithms
Version: 0.1
Date: 2016-02-11
Author: Somenath Sit
Maintainer: Somenath Sit <somenath.bhu.2010@gmail.com>
Description: Implementation of two transportation problem algorithms. 1. North West Corner Method 2. Minimum Cost Method or Least cost method. For more technical details about the algorithms please refer below URLs. <http://www.universalteacherpublications.com/univ/ebooks/or/Ch5/nw.htm>. <http://personal.maths.surrey.ac.uk/st/J.F/chapter7.pdf>.
License: GPL (>= 2)
LazyLoad: yes
RoxygenNote: 5.0.1
URL: https://github.com/Somenath24/TransP
NeedsCompilation: no
Packaged: 2016-02-13 05:28:10 UTC; Somenath
Repository: CRAN
Date/Publication: 2016-02-13 19:01:12

More information about TransP at CRAN
Permanent link

Package rstanarm updated to version 2.9.0-3 with previous version 2.9.0-1 dated 2016-01-09

Title: Bayesian Applied Regression Modeling via Stan
Description: Estimates pre-compiled regression models using the 'rstan' package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.
Author: Jonah Gabry [aut], Trustees of Columbia University [cph], R Core Deveopment Team [cph] (R/pp_data.R, R/stan_aov.R), Douglas Bates [cph] (R/pp_data.R), Martin Maechler [cph] (R/pp_data.R), Ben Bolker [cph] (R/pp_data.R), Steve Walker [cph] (R/pp_data.R), Brian Ripley [cph] (R/stan_aov.R, R/stan_polr.R), William Venables [cph] (R/stan_polr.R), Ben Goodrich [cre, aut]
Maintainer: Ben Goodrich <benjamin.goodrich@columbia.edu>

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Package RNetCDF updated to version 1.8-1 with previous version 1.7-3 dated 2015-05-11

Title: Interface to NetCDF Datasets
Description: An interface to the NetCDF file format designed by Unidata for efficient storage of array-oriented scientific data and descriptions. The R interface is closely based on the C API of the NetCDF library, and it includes calendar conversions from the Unidata UDUNITS library. The current implementation supports all operations on NetCDF datasets in classic and 64-bit offset file formats, and NetCDF4-classic format is supported for reading and modification of existing files.
Author: Pavel Michna, with contributions from Milton Woods
Maintainer: Milton Woods <mwoods@users.r-forge.r-project.org>

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Package rgeos updated to version 0.3-17 with previous version 0.3-15 dated 2015-11-04

Title: Interface to Geometry Engine - Open Source (GEOS)
Description: Interface to Geometry Engine - Open Source (GEOS) using the C API for topology operations on geometries. The GEOS library is external to the package, and, when installing the package from source, must be correctly installed first. Windows and Mac Intel OS X binaries are provided on CRAN.
Author: Roger Bivand [cre, aut], Colin Rundel [aut], Edzer Pebesma [ctb], Karl Ove Hufthammer [ctb]
Maintainer: Roger Bivand <Roger.Bivand@nhh.no>

Diff between rgeos versions 0.3-15 dated 2015-11-04 and 0.3-17 dated 2016-02-13

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Package qrmtools updated to version 0.0-5 with previous version 0.0-4 dated 2016-01-15

Title: Tools for Quantitative Risk Management
Description: Functions and data sets for reproducing selected results from the book "Quantitative Risk Management: Concepts, Techniques and Tools". Furthermore, new developments and auxiliary functions for Quantitative Risk Management practice.
Author: Marius Hofert [aut, cre], Kurt Hornik [aut]
Maintainer: Marius Hofert <marius.hofert@uwaterloo.ca>

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Package pcadapt updated to version 2.2 with previous version 2.1.1 dated 2016-01-05

Title: Principal Component Analysis for Outlier Detection
Description: Methods to detect genetic markers involved in biological adaptation. 'pcadapt' provides statistical tools for outlier detection based on Principal Component Analysis.
Author: Keurcien Luu, Michael G.B. Blum
Maintainer: Keurcien Luu <keurcien.luu@imag.fr>

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New package nproc with initial version 0.1
Package: nproc
Type: Package
Title: Neyman-Pearson Receiver Operator Curve
Version: 0.1
Date: 2016-02-11
Author: Yang Feng, Jessica Li and Xin Tong
Maintainer: Yang Feng <yang.feng@columbia.edu>
Imports: glmnet, e1071, randomForest, MASS, parallel, ada, stats, graphics
Description: Given a sample of class 0 and class 1 and a classification method, the package generates the corresponding Neyman-Pearson classifier with a pre-specified type-I error control and Neyman-Pearson Receiver Operator Curve.
License: GPL-2
LazyData: TRUE
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-02-13 03:37:51 UTC; yangfeng
Repository: CRAN
Date/Publication: 2016-02-13 19:01:18

More information about nproc at CRAN
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Package maps updated to version 3.1.0 with previous version 3.0.2 dated 2016-01-04

Title: Draw Geographical Maps
Description: Display of maps. Projection code and larger maps are in separate packages ('mapproj' and 'mapdata').
Author: Original S code by Richard A. Becker and Allan R. Wilks. R version by Ray Brownrigg. Enhancements by Thomas P Minka and Alex Deckmyn.
Maintainer: Alex Deckmyn <alex.deckmyn@meteo.be>

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More information about maps at CRAN
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Package mlr updated to version 2.8 with previous version 2.7 dated 2015-12-04

Title: Machine Learning in R
Description: Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques, for single- and multi-objective problems. Filter and wrapper methods for feature selection. Extension of basic learners with additional operations common in machine learning, also allowing for easy nested resampling. Most operations can be parallelized.
Author: Bernd Bischl [aut, cre], Michel Lang [aut], Jakob Richter [aut], Jakob Bossek [aut], Leonard Judt [aut], Tobias Kuehn [aut], Erich Studerus [aut], Lars Kotthoff [aut], Zachary Jones [ctb], Schiffner Julia [aut]
Maintainer: Bernd Bischl <bernd_bischl@gmx.net>

Diff between mlr versions 2.7 dated 2015-12-04 and 2.8 dated 2016-02-13

 mlr-2.7/mlr/R/benchmarkTest.R                                    |only
 mlr-2.7/mlr/R/checkColumnNames.R                                 |only
 mlr-2.7/mlr/R/checkDfTarget.R                                    |only
 mlr-2.7/mlr/R/generateCritDifferences.R                          |only
 mlr-2.7/mlr/R/generateROCRCurves.R                               |only
 mlr-2.7/mlr/man/FilterValues.Rd                                  |only
 mlr-2.7/mlr/man/LearningCurveData.Rd                             |only
 mlr-2.7/mlr/man/PartialPredictionData.Rd                         |only
 mlr-2.7/mlr/man/generateROCRCurvesData.Rd                        |only
 mlr-2.7/mlr/man/plotROCRCurves.Rd                                |only
 mlr-2.7/mlr/man/plotROCRCurvesGGVIS.Rd                           |only
 mlr-2.7/mlr/tests/run-learners.R                                 |only
 mlr-2.7/mlr/tests/testthat/test_base_BMRhypothesisTests.R        |only
 mlr-2.7/mlr/tests/testthat/test_regr_randomForest_se.R           |only
 mlr-2.8/mlr/DESCRIPTION                                          |   22 
 mlr-2.8/mlr/MD5                                                  |  660 +++++-----
 mlr-2.8/mlr/NAMESPACE                                            |   42 
 mlr-2.8/mlr/NEWS                                                 |   44 
 mlr-2.8/mlr/R/Aggregation.R                                      |   41 
 mlr-2.8/mlr/R/BaseEnsemble.R                                     |    7 
 mlr-2.8/mlr/R/BenchmarkResult_operators.R                        |   39 
 mlr-2.8/mlr/R/CostSensTask.R                                     |    4 
 mlr-2.8/mlr/R/CostSensWeightedPairsWrapper.R                     |    3 
 mlr-2.8/mlr/R/Filter.R                                           |   43 
 mlr-2.8/mlr/R/ImputeMethods.R                                    |    3 
 mlr-2.8/mlr/R/Learner_properties.R                               |   32 
 mlr-2.8/mlr/R/Measure.R                                          |   18 
 mlr-2.8/mlr/R/Measure_custom_resampled.R                         |   11 
 mlr-2.8/mlr/R/ModelMultiplexer.R                                 |   11 
 mlr-2.8/mlr/R/MulticlassWrapper.R                                |   14 
 mlr-2.8/mlr/R/OverBaggingWrapper.R                               |   34 
 mlr-2.8/mlr/R/OverUnderSampling.R                                |   34 
 mlr-2.8/mlr/R/OverUndersampleWrapper.R                           |   36 
 mlr-2.8/mlr/R/PreprocWrapperCaret.R                              |    2 
 mlr-2.8/mlr/R/RLearner.R                                         |   51 
 mlr-2.8/mlr/R/RLearner_classif_J48.R                             |    2 
 mlr-2.8/mlr/R/RLearner_classif_JRip.R                            |    2 
 mlr-2.8/mlr/R/RLearner_classif_LiblineaRL2LogReg.R               |    7 
 mlr-2.8/mlr/R/RLearner_classif_LiblineaRL2SVC.R                  |    5 
 mlr-2.8/mlr/R/RLearner_classif_OneR.R                            |    2 
 mlr-2.8/mlr/R/RLearner_classif_PART.R                            |    2 
 mlr-2.8/mlr/R/RLearner_classif_ada.R                             |    6 
 mlr-2.8/mlr/R/RLearner_classif_avNNet.R                          |    2 
 mlr-2.8/mlr/R/RLearner_classif_bartMachine.R                     |    2 
 mlr-2.8/mlr/R/RLearner_classif_binomial.R                        |    2 
 mlr-2.8/mlr/R/RLearner_classif_blackboost.R                      |    2 
 mlr-2.8/mlr/R/RLearner_classif_boosting.R                        |    4 
 mlr-2.8/mlr/R/RLearner_classif_bst.R                             |    6 
 mlr-2.8/mlr/R/RLearner_classif_cforest.R                         |   10 
 mlr-2.8/mlr/R/RLearner_classif_clusterSVM.R                      |    2 
 mlr-2.8/mlr/R/RLearner_classif_ctree.R                           |    2 
 mlr-2.8/mlr/R/RLearner_classif_cvglmnet.R                        |only
 mlr-2.8/mlr/R/RLearner_classif_dbnDNN.R                          |    2 
 mlr-2.8/mlr/R/RLearner_classif_gaterSVM.R                        |    2 
 mlr-2.8/mlr/R/RLearner_classif_gbm.R                             |    5 
 mlr-2.8/mlr/R/RLearner_classif_geoDA.R                           |    3 
 mlr-2.8/mlr/R/RLearner_classif_glmboost.R                        |    2 
 mlr-2.8/mlr/R/RLearner_classif_glmnet.R                          |    5 
 mlr-2.8/mlr/R/RLearner_classif_ksvm.R                            |    2 
 mlr-2.8/mlr/R/RLearner_classif_lda.R                             |    2 
 mlr-2.8/mlr/R/RLearner_classif_linDA.R                           |    6 
 mlr-2.8/mlr/R/RLearner_classif_logreg.R                          |    2 
 mlr-2.8/mlr/R/RLearner_classif_lqa.R                             |    2 
 mlr-2.8/mlr/R/RLearner_classif_mda.R                             |    2 
 mlr-2.8/mlr/R/RLearner_classif_nnTrain.R                         |    2 
 mlr-2.8/mlr/R/RLearner_classif_nnet.R                            |    2 
 mlr-2.8/mlr/R/RLearner_classif_pamr.R                            |    2 
 mlr-2.8/mlr/R/RLearner_classif_plr.R                             |    2 
 mlr-2.8/mlr/R/RLearner_classif_probit.R                          |    2 
 mlr-2.8/mlr/R/RLearner_classif_qda.R                             |    2 
 mlr-2.8/mlr/R/RLearner_classif_quaDA.R                           |    4 
 mlr-2.8/mlr/R/RLearner_classif_randomForest.R                    |    5 
 mlr-2.8/mlr/R/RLearner_classif_randomForestSRC.R                 |    2 
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 mlr-2.8/mlr/R/RLearner_classif_rpart.R                           |    4 
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 mlr-2.8/mlr/R/RLearner_classif_sparseLDA.R                       |    2 
 mlr-2.8/mlr/R/RLearner_classif_svm.R                             |    3 
 mlr-2.8/mlr/R/RLearner_classif_xgboost.R                         |   11 
 mlr-2.8/mlr/R/RLearner_cluster_XMeans.R                          |    2 
 mlr-2.8/mlr/R/RLearner_cluster_cmeans.R                          |    2 
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 mlr-2.8/mlr/R/RLearner_cluster_kmeans.R                          |    2 
 mlr-2.8/mlr/R/RLearner_regr_LiblineaRL2L1SVR.R                   |    2 
 mlr-2.8/mlr/R/RLearner_regr_LiblineaRL2L2SVR.R                   |    4 
 mlr-2.8/mlr/R/RLearner_regr_avNNet.R                             |    2 
 mlr-2.8/mlr/R/RLearner_regr_bartMachine.R                        |    2 
 mlr-2.8/mlr/R/RLearner_regr_blackBoost.R                         |    2 
 mlr-2.8/mlr/R/RLearner_regr_bst.R                                |    6 
 mlr-2.8/mlr/R/RLearner_regr_cforest.R                            |   10 
 mlr-2.8/mlr/R/RLearner_regr_ctree.R                              |    2 
 mlr-2.8/mlr/R/RLearner_regr_elmNN.R                              |    2 
 mlr-2.8/mlr/R/RLearner_regr_gbm.R                                |    4 
 mlr-2.8/mlr/R/RLearner_regr_glmboost.R                           |    2 
 mlr-2.8/mlr/R/RLearner_regr_glmnet.R                             |    5 
 mlr-2.8/mlr/R/RLearner_regr_km.R                                 |    2 
 mlr-2.8/mlr/R/RLearner_regr_ksvm.R                               |    2 
 mlr-2.8/mlr/R/RLearner_regr_nnet.R                               |    2 
 mlr-2.8/mlr/R/RLearner_regr_randomForest.R                       |  193 +-
 mlr-2.8/mlr/R/RLearner_regr_randomForestSRC.R                    |    6 
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 mlr-2.8/mlr/R/RLearner_regr_ranger.R                             |    2 
 mlr-2.8/mlr/R/RLearner_regr_rpart.R                              |    4 
 mlr-2.8/mlr/R/RLearner_regr_rsm.R                                |    2 
 mlr-2.8/mlr/R/RLearner_regr_rvm.R                                |    6 
 mlr-2.8/mlr/R/RLearner_regr_slim.R                               |    2 
 mlr-2.8/mlr/R/RLearner_regr_svm.R                                |    2 
 mlr-2.8/mlr/R/RLearner_regr_xgboost.R                            |    7 
 mlr-2.8/mlr/R/RLearner_surv_CoxBoost.R                           |    2 
 mlr-2.8/mlr/R/RLearner_surv_cforest.R                            |   10 
 mlr-2.8/mlr/R/RLearner_surv_cvglmnet.R                           |    5 
 mlr-2.8/mlr/R/RLearner_surv_glmboost.R                           |    2 
 mlr-2.8/mlr/R/RLearner_surv_glmnet.R                             |    5 
 mlr-2.8/mlr/R/RLearner_surv_optimCoxBoostPenalty.R               |    2 
 mlr-2.8/mlr/R/RLearner_surv_penalized.R                          |    2 
 mlr-2.8/mlr/R/RLearner_surv_ranger.R                             |    2 
 mlr-2.8/mlr/R/RLearner_surv_rpart.R                              |    4 
 mlr-2.8/mlr/R/ResampleDesc.R                                     |    8 
 mlr-2.8/mlr/R/ResampleInstances.R                                |    2 
 mlr-2.8/mlr/R/StackedLearner.R                                   |   62 
 mlr-2.8/mlr/R/Task.R                                             |   23 
 mlr-2.8/mlr/R/TaskDesc.R                                         |   22 
 mlr-2.8/mlr/R/Task_operators.R                                   |   19 
 mlr-2.8/mlr/R/WrappedModel.R                                     |    2 
 mlr-2.8/mlr/R/aggregations.R                                     |    2 
 mlr-2.8/mlr/R/benchmark.R                                        |    2 
 mlr-2.8/mlr/R/benchmarkResult_mergers.R                          |   12 
 mlr-2.8/mlr/R/capLargeValues.R                                   |   27 
 mlr-2.8/mlr/R/checkPrediction.R                                  |    2 
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 mlr-2.8/mlr/R/convertBMRToRankMatrix.R                           |   13 
 mlr-2.8/mlr/R/convertX.R                                         |    9 
 mlr-2.8/mlr/R/crossover.R                                        |    2 
 mlr-2.8/mlr/R/datasets.R                                         |   22 
 mlr-2.8/mlr/R/estimateResidualVariance.R                         |    9 
 mlr-2.8/mlr/R/evalOptimizationState.R                            |    9 
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 mlr-2.8/mlr/R/generateCalibration.R                              |   26 
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 mlr-2.8/mlr/R/generateThreshVsPerf.R                             |  219 ++-
 mlr-2.8/mlr/R/getClassWeightParam.R                              |    5 
 mlr-2.8/mlr/R/helpers.R                                          |   15 
 mlr-2.8/mlr/R/listLearners.R                                     |   53 
 mlr-2.8/mlr/R/logFunOpt.R                                        |    2 
 mlr-2.8/mlr/R/makeLearner.R                                      |    5 
 mlr-2.8/mlr/R/measures.R                                         |   60 
 mlr-2.8/mlr/R/normalizeFeatures.R                                |    2 
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 mlr-2.8/mlr/man/benchmark.Rd                                     |    7 
 mlr-2.8/mlr/man/bh.task.Rd                                       |    2 
 mlr-2.8/mlr/man/capLargeValues.Rd                                |   12 
 mlr-2.8/mlr/man/convertBMRToRankMatrix.Rd                        |   17 
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 mlr-2.8/mlr/tests/testthat/test_base_benchmark.R                 |   16 
 mlr-2.8/mlr/tests/testthat/test_base_benchmark_merger.R          |    2 
 mlr-2.8/mlr/tests/testthat/test_base_capLargeValues.R            |   20 
 mlr-2.8/mlr/tests/testthat/test_base_clustering.R                |    2 
 mlr-2.8/mlr/tests/testthat/test_base_convertBMRToRankMatrix.R    |    2 
 mlr-2.8/mlr/tests/testthat/test_base_downsample.R                |    1 
 mlr-2.8/mlr/tests/testthat/test_base_friedmanTestBMR.R           |only
 mlr-2.8/mlr/tests/testthat/test_base_generateCalibration.R       |   18 
 mlr-2.8/mlr/tests/testthat/test_base_generateLearningCurve.R     |   18 
 mlr-2.8/mlr/tests/testthat/test_base_generatePartialPrediction.R |   81 -
 mlr-2.8/mlr/tests/testthat/test_base_generateThreshVsPerf.R      |   51 
 mlr-2.8/mlr/tests/testthat/test_base_imbal_overbagging.R         |   21 
 mlr-2.8/mlr/tests/testthat/test_base_imbal_overundersample.R     |   35 
 mlr-2.8/mlr/tests/testthat/test_base_imbal_weightedclasses.R     |    2 
 mlr-2.8/mlr/tests/testthat/test_base_impute.R                    |    2 
 mlr-2.8/mlr/tests/testthat/test_base_listLearners.R              |only
 mlr-2.8/mlr/tests/testthat/test_base_measures.R                  |  179 +-
 mlr-2.8/mlr/tests/testthat/test_base_orderBMRLevels.R            |    2 
 mlr-2.8/mlr/tests/testthat/test_base_orderedfactors.R            |    2 
 mlr-2.8/mlr/tests/testthat/test_base_plotBMRBoxplots.R           |    4 
 mlr-2.8/mlr/tests/testthat/test_base_plotBMRSummary.R            |    2 
 mlr-2.8/mlr/tests/testthat/test_base_plotCritDifferences.R       |   46 
 mlr-2.8/mlr/tests/testthat/test_base_prediction_operators.R      |    2 
 mlr-2.8/mlr/tests/testthat/test_base_resample_b632.R             |    2 
 mlr-2.8/mlr/tests/testthat/test_base_resample_b632plus.R         |    2 
 mlr-2.8/mlr/tests/testthat/test_base_resample_bs.R               |    2 
 mlr-2.8/mlr/tests/testthat/test_base_resample_convenience.R      |    2 
 mlr-2.8/mlr/tests/testthat/test_base_resample_cv.R               |    2 
 mlr-2.8/mlr/tests/testthat/test_base_resample_dps.R              |    2 
 mlr-2.8/mlr/tests/testthat/test_base_resample_holdout.R          |    2 
 mlr-2.8/mlr/tests/testthat/test_base_resample_loo.R              |    2 
 mlr-2.8/mlr/tests/testthat/test_base_resample_repcv.R            |    2 
 mlr-2.8/mlr/tests/testthat/test_base_resample_stratify.R         |    2 
 mlr-2.8/mlr/tests/testthat/test_base_resample_subsample.R        |    2 
 mlr-2.8/mlr/tests/testthat/test_base_resample_weights.R          |    2 
 mlr-2.8/mlr/tests/testthat/test_base_rocr.R                      |   28 
 mlr-2.8/mlr/tests/testthat/test_base_selectFeatures.R            |    2 
 mlr-2.8/mlr/tests/testthat/test_base_tuning.R                    |    2 
 mlr-2.8/mlr/tests/testthat/test_classif_LibLineaRMultiClassSVC.R |   32 
 mlr-2.8/mlr/tests/testthat/test_classif_LiblineaRL1L2SVC.R       |   32 
 mlr-2.8/mlr/tests/testthat/test_classif_LiblineaRL1LogReg.R      |   36 
 mlr-2.8/mlr/tests/testthat/test_classif_LiblineaRL2L1SVC.R       |   32 
 mlr-2.8/mlr/tests/testthat/test_classif_LiblineaRL2LogReg.R      |   43 
 mlr-2.8/mlr/tests/testthat/test_classif_LiblineaRL2SVC.R         |   38 
 mlr-2.8/mlr/tests/testthat/test_classif_cforest.R                |    9 
 mlr-2.8/mlr/tests/testthat/test_classif_cvglmnet.R               |only
 mlr-2.8/mlr/tests/testthat/test_classif_glmnet.R                 |    2 
 mlr-2.8/mlr/tests/testthat/test_classif_randomForestSRCSyn.R     |only
 mlr-2.8/mlr/tests/testthat/test_cluster_dbscan.R                 |only
 mlr-2.8/mlr/tests/testthat/test_featsel_FilterWrapper.R          |    8 
 mlr-2.8/mlr/tests/testthat/test_featsel_filterFeatures.R         |   14 
 mlr-2.8/mlr/tests/testthat/test_learners_all_classif.R           |    9 
 mlr-2.8/mlr/tests/testthat/test_learners_all_clusters.R          |    6 
 mlr-2.8/mlr/tests/testthat/test_learners_all_general.R           |   30 
 mlr-2.8/mlr/tests/testthat/test_learners_all_regr.R              |   12 
 mlr-2.8/mlr/tests/testthat/test_learners_classiflabelswitch.R    |    1 
 mlr-2.8/mlr/tests/testthat/test_parallel_all.R                   |    2 
 mlr-2.8/mlr/tests/testthat/test_regr_LiblineaRL2L1SVR.R          |   32 
 mlr-2.8/mlr/tests/testthat/test_regr_LiblineaRL2L2SVR.R          |   38 
 mlr-2.8/mlr/tests/testthat/test_regr_cforest.R                   |    6 
 mlr-2.8/mlr/tests/testthat/test_regr_randomForest.R              |   17 
 mlr-2.8/mlr/tests/testthat/test_regr_randomForestSRC.R           |    3 
 mlr-2.8/mlr/tests/testthat/test_regr_randomForestSRCSyn.R        |only
 mlr-2.8/mlr/tests/testthat/test_stack.R                          |   10 
 mlr-2.8/mlr/tests/testthat/test_surv_cforest.R                   |    7 
 mlr-2.8/mlr/tests/testthat/test_surv_cvglmnet.R                  |    2 
 mlr-2.8/mlr/tests/testthat/test_tune_ModelMultiplexer.R          |   34 
 mlr-2.8/mlr/tests/testthat/test_tune_tuneIrace.R                 |   19 
 mlr-2.8/mlr/tests/testthat/test_tune_tuneMBO.R                   |   22 
 349 files changed, 2874 insertions(+), 2227 deletions(-)

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