##Процесс выполнения:

R version 4.4.2 (2024-10-31 ucrt) – “Pile of Leaves” Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64

R – это свободное ПО, и оно поставляется безо всяких гарантий. Вы вольны распространять его при соблюдении некоторых условий. Введите ‘license()’ для получения более подробной информации.

R – это проект, в котором сотрудничает множество разработчиков. Введите ‘contributors()’ для получения дополнительной информации и ‘citation()’ для ознакомления с правилами упоминания R и его пакетов в публикациях.

Введите ‘demo()’ для запуска демонстрационных программ, ‘help()’ – для получения справки, ‘help.start()’ – для доступа к справке через браузер. Введите ‘q()’, чтобы выйти из R.

[Workspace loaded from ~/.RData]

knitr::opts_chunk\(set(echo = TRUE) plot(pressure) knitr::opts_chunk\)set(echo = TRUE) names(getModelInfo()) Ошибка в getModelInfo() : не могу найти функцию “getModelInfo” library(caret) Ошибка в library(caret) : нет пакета под названием ‘caret’ install.packages(‘caret’) WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:

https://cran.rstudio.com/bin/windows/Rtools/ Устанавливаю пакет в ‘C:/Users/Евдик/AppData/Local/R/win-library/4.4’ (потому что ‘lib’ не определено) устанавливаю также зависимости ‘listenv’, ‘parallelly’, ‘future’, ‘globals’, ‘shape’, ‘future.apply’, ‘numDeriv’, ‘progressr’, ‘SQUAREM’, ‘diagram’, ‘lava’, ‘tzdb’, ‘cpp11’, ‘prodlim’, ‘timechange’, ‘proxy’, ‘iterators’, ‘Rcpp’, ‘data.table’, ‘dplyr’, ‘clock’, ‘generics’, ‘gower’, ‘hardhat’, ‘ipred’, ‘lubridate’, ‘purrr’, ‘sparsevctrs’, ‘tidyr’, ‘tidyselect’, ‘timeDate’, ‘e1071’, ‘foreach’, ‘ModelMetrics’, ‘plyr’, ‘pROC’, ‘recipes’, ‘reshape2’

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/listenv_0.9.1.zip’ Content type ‘application/zip’ length 110022 bytes (107 KB) downloaded 107 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/parallelly_1.42.0.zip’ Content type ‘application/zip’ length 569315 bytes (555 KB) downloaded 555 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/future_1.34.0.zip’ Content type ‘application/zip’ length 692936 bytes (676 KB) downloaded 676 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/globals_0.16.3.zip’ Content type ‘application/zip’ length 109926 bytes (107 KB) downloaded 107 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/shape_1.4.6.1.zip’ Content type ‘application/zip’ length 753988 bytes (736 KB) downloaded 736 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/future.apply_1.11.3.zip’ Content type ‘application/zip’ length 160711 bytes (156 KB) downloaded 156 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/numDeriv_2016.8-1.1.zip’ Content type ‘application/zip’ length 117304 bytes (114 KB) downloaded 114 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/progressr_0.15.1.zip’ Content type ‘application/zip’ length 403781 bytes (394 KB) downloaded 394 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/SQUAREM_2021.1.zip’ Content type ‘application/zip’ length 183502 bytes (179 KB) downloaded 179 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/diagram_1.6.5.zip’ Content type ‘application/zip’ length 688009 bytes (671 KB) downloaded 671 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/lava_1.8.1.zip’ Content type ‘application/zip’ length 2516019 bytes (2.4 MB) downloaded 2.4 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/tzdb_0.5.0.zip’ Content type ‘application/zip’ length 1038731 bytes (1014 KB) downloaded 1014 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/cpp11_0.5.2.zip’ Content type ‘application/zip’ length 310790 bytes (303 KB) downloaded 303 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/prodlim_2024.06.25.zip’ Content type ‘application/zip’ length 425191 bytes (415 KB) downloaded 415 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/timechange_0.3.0.zip’ Content type ‘application/zip’ length 516671 bytes (504 KB) downloaded 504 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/proxy_0.4-27.zip’ Content type ‘application/zip’ length 181355 bytes (177 KB) downloaded 177 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/iterators_1.0.14.zip’ Content type ‘application/zip’ length 353853 bytes (345 KB) downloaded 345 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/Rcpp_1.0.14.zip’ Content type ‘application/zip’ length 2901278 bytes (2.8 MB) downloaded 2.8 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/data.table_1.17.0.zip’ Content type ‘application/zip’ length 2910370 bytes (2.8 MB) downloaded 2.8 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/dplyr_1.1.4.zip’ Content type ‘application/zip’ length 1590630 bytes (1.5 MB) downloaded 1.5 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/clock_0.7.2.zip’ Content type ‘application/zip’ length 2227344 bytes (2.1 MB) downloaded 2.1 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/generics_0.1.3.zip’ Content type ‘application/zip’ length 86334 bytes (84 KB) downloaded 84 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/gower_1.0.2.zip’ Content type ‘application/zip’ length 326588 bytes (318 KB) downloaded 318 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/hardhat_1.4.1.zip’ Content type ‘application/zip’ length 875354 bytes (854 KB) downloaded 854 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/ipred_0.9-15.zip’ Content type ‘application/zip’ length 393385 bytes (384 KB) downloaded 384 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/lubridate_1.9.4.zip’ Content type ‘application/zip’ length 990431 bytes (967 KB) downloaded 967 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/purrr_1.0.4.zip’ Content type ‘application/zip’ length 550905 bytes (537 KB) downloaded 537 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/sparsevctrs_0.3.1.zip’ Content type ‘application/zip’ length 204561 bytes (199 KB) downloaded 199 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/tidyr_1.3.1.zip’ Content type ‘application/zip’ length 1273623 bytes (1.2 MB) downloaded 1.2 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/tidyselect_1.2.1.zip’ Content type ‘application/zip’ length 229157 bytes (223 KB) downloaded 223 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/timeDate_4041.110.zip’ Content type ‘application/zip’ length 1406591 bytes (1.3 MB) downloaded 1.3 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/e1071_1.7-16.zip’ Content type ‘application/zip’ length 674236 bytes (658 KB) downloaded 658 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/foreach_1.5.2.zip’ Content type ‘application/zip’ length 149903 bytes (146 KB) downloaded 146 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/ModelMetrics_1.2.2.2.zip’ Content type ‘application/zip’ length 480531 bytes (469 KB) downloaded 469 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/plyr_1.8.9.zip’ Content type ‘application/zip’ length 1112935 bytes (1.1 MB) downloaded 1.1 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/pROC_1.18.5.zip’ Content type ‘application/zip’ length 1168419 bytes (1.1 MB) downloaded 1.1 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/recipes_1.2.0.zip’ Content type ‘application/zip’ length 1728035 bytes (1.6 MB) downloaded 1.6 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/reshape2_1.4.4.zip’ Content type ‘application/zip’ length 442611 bytes (432 KB) downloaded 432 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/caret_7.0-1.zip’ Content type ‘application/zip’ length 3603209 bytes (3.4 MB) downloaded 3.4 MB

пакет ‘listenv’ успешно распакован, MD5-суммы проверены пакет ‘parallelly’ успешно распакован, MD5-суммы проверены пакет ‘future’ успешно распакован, MD5-суммы проверены пакет ‘globals’ успешно распакован, MD5-суммы проверены пакет ‘shape’ успешно распакован, MD5-суммы проверены пакет ‘future.apply’ успешно распакован, MD5-суммы проверены пакет ‘numDeriv’ успешно распакован, MD5-суммы проверены пакет ‘progressr’ успешно распакован, MD5-суммы проверены пакет ‘SQUAREM’ успешно распакован, MD5-суммы проверены пакет ‘diagram’ успешно распакован, MD5-суммы проверены пакет ‘lava’ успешно распакован, MD5-суммы проверены пакет ‘tzdb’ успешно распакован, MD5-суммы проверены пакет ‘cpp11’ успешно распакован, MD5-суммы проверены пакет ‘prodlim’ успешно распакован, MD5-суммы проверены пакет ‘timechange’ успешно распакован, MD5-суммы проверены пакет ‘proxy’ успешно распакован, MD5-суммы проверены пакет ‘iterators’ успешно распакован, MD5-суммы проверены пакет ‘Rcpp’ успешно распакован, MD5-суммы проверены пакет ‘data.table’ успешно распакован, MD5-суммы проверены пакет ‘dplyr’ успешно распакован, MD5-суммы проверены пакет ‘clock’ успешно распакован, MD5-суммы проверены пакет ‘generics’ успешно распакован, MD5-суммы проверены пакет ‘gower’ успешно распакован, MD5-суммы проверены пакет ‘hardhat’ успешно распакован, MD5-суммы проверены пакет ‘ipred’ успешно распакован, MD5-суммы проверены пакет ‘lubridate’ успешно распакован, MD5-суммы проверены пакет ‘purrr’ успешно распакован, MD5-суммы проверены пакет ‘sparsevctrs’ успешно распакован, MD5-суммы проверены пакет ‘tidyr’ успешно распакован, MD5-суммы проверены пакет ‘tidyselect’ успешно распакован, MD5-суммы проверены пакет ‘timeDate’ успешно распакован, MD5-суммы проверены пакет ‘e1071’ успешно распакован, MD5-суммы проверены пакет ‘foreach’ успешно распакован, MD5-суммы проверены пакет ‘ModelMetrics’ успешно распакован, MD5-суммы проверены пакет ‘plyr’ успешно распакован, MD5-суммы проверены пакет ‘pROC’ успешно распакован, MD5-суммы проверены пакет ‘recipes’ успешно распакован, MD5-суммы проверены пакет ‘reshape2’ успешно распакован, MD5-суммы проверены пакет ‘caret’ успешно распакован, MD5-суммы проверены

Скачанные бинарные пакеты находятся в C:_packages > names(getModelInfo()) Ошибка в getModelInfo() : не могу найти функцию “getModelInfo” > library(caret) Загрузка требуемого пакета: ggplot2 Keep up to date with changes at https://tidyverse.org/blog/

Присоединяю пакет: ‘ggplot2’

Следующий объект скрыт ‘.GlobalEnv’:

diamonds

Загрузка требуемого пакета: lattice Предупреждение: пакет ‘caret’ был собран под R версии 4.4.3 > names(getModelInfo()) [1] “ada” “AdaBag” “AdaBoost.M1”
[4] “adaboost” “amdai” “ANFIS”
[7] “avNNet” “awnb” “awtan”
[10] “bag” “bagEarth” “bagEarthGCV”
[13] “bagFDA” “bagFDAGCV” “bam”
[16] “bartMachine” “bayesglm” “binda”
[19] “blackboost” “blasso” “blassoAveraged”
[22] “bridge” “brnn” “BstLm”
[25] “bstSm” “bstTree” “C5.0”
[28] “C5.0Cost” “C5.0Rules” “C5.0Tree”
[31] “cforest” “chaid” “CSimca”
[34] “ctree” “ctree2” “cubist”
[37] “dda” “deepboost” “DENFIS”
[40] “dnn” “dwdLinear” “dwdPoly”
[43] “dwdRadial” “earth” “elm”
[46] “enet” “evtree” “extraTrees”
[49] “fda” “FH.GBML” “FIR.DM”
[52] “foba” “FRBCS.CHI” “FRBCS.W”
[55] “FS.HGD” “gam” “gamboost”
[58] “gamLoess” “gamSpline” “gaussprLinear”
[61] “gaussprPoly” “gaussprRadial” “gbm_h2o”
[64] “gbm” “gcvEarth” “GFS.FR.MOGUL”
[67] “GFS.LT.RS” “GFS.THRIFT” “glm.nb”
[70] “glm” “glmboost” “glmnet_h2o”
[73] “glmnet” “glmStepAIC” “gpls”
[76] “hda” “hdda” “hdrda”
[79] “HYFIS” “icr” “J48”
[82] “JRip” “kernelpls” “kknn”
[85] “knn” “krlsPoly” “krlsRadial”
[88] “lars” “lars2” “lasso”
[91] “lda” “lda2” “leapBackward”
[94] “leapForward” “leapSeq” “Linda”
[97] “lm” “lmStepAIC” “LMT”
[100] “loclda” “logicBag” “LogitBoost”
[103] “logreg” “lssvmLinear” “lssvmPoly”
[106] “lssvmRadial” “lvq” “M5”
[109] “M5Rules” “manb” “mda”
[112] “Mlda” “mlp” “mlpKerasDecay”
[115] “mlpKerasDecayCost” “mlpKerasDropout” “mlpKerasDropoutCost” [118] “mlpML” “mlpSGD” “mlpWeightDecay”
[121] “mlpWeightDecayML” “monmlp” “msaenet”
[124] “multinom” “mxnet” “mxnetAdam”
[127] “naive_bayes” “nb” “nbDiscrete”
[130] “nbSearch” “neuralnet” “nnet”
[133] “nnls” “nodeHarvest” “null”
[136] “OneR” “ordinalNet” “ordinalRF”
[139] “ORFlog” “ORFpls” “ORFridge”
[142] “ORFsvm” “ownn” “pam”
[145] “parRF” “PART” “partDSA”
[148] “pcaNNet” “pcr” “pda”
[151] “pda2” “penalized” “PenalizedLDA”
[154] “plr” “pls” “plsRglm”
[157] “polr” “ppr” “pre”
[160] “PRIM” “protoclass” “qda”
[163] “QdaCov” “qrf” “qrnn”
[166] “randomGLM” “ranger” “rbf”
[169] “rbfDDA” “Rborist” “rda”
[172] “regLogistic” “relaxo” “rf”
[175] “rFerns” “RFlda” “rfRules”
[178] “ridge” “rlda” “rlm”
[181] “rmda” “rocc” “rotationForest”
[184] “rotationForestCp” “rpart” “rpart1SE”
[187] “rpart2” “rpartCost” “rpartScore”
[190] “rqlasso” “rqnc” “RRF”
[193] “RRFglobal” “rrlda” “RSimca”
[196] “rvmLinear” “rvmPoly” “rvmRadial”
[199] “SBC” “sda” “sdwd”
[202] “simpls” “SLAVE” “slda”
[205] “smda” “snn” “sparseLDA”
[208] “spikeslab” “spls” “stepLDA”
[211] “stepQDA” “superpc” “svmBoundrangeString” [214] “svmExpoString” “svmLinear” “svmLinear2”
[217] “svmLinear3” “svmLinearWeights” “svmLinearWeights2”
[220] “svmPoly” “svmRadial” “svmRadialCost”
[223] “svmRadialSigma” “svmRadialWeights” “svmSpectrumString”
[226] “tan” “tanSearch” “treebag”
[229] “vbmpRadial” “vglmAdjCat” “vglmContRatio”
[232] “vglmCumulative” “widekernelpls” “WM”
[235] “wsrf” “xgbDART” “xgbLinear”
[238] “xgbTree” “xyf”
> x <- matrix(rnorm(50*5),ncol=5) > y <- factor(rep(c(“A”, “B”), 25)) > featurePlot(x,y) > featurePlot(x) Ошибка в featurePlot(x) : аргумент “y” пропущен, умолчаний нет > install.packages(‘Fselector’) WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:

https://cran.rstudio.com/bin/windows/Rtools/ Устанавливаю пакет в ‘C:/Users/Евдик/AppData/Local/R/win-library/4.4’ (потому что ‘lib’ не определено) Warning in install.packages : пакет ‘‘Fselector’’ недоступен (for this version of R

Другая версия этого пакета может быть доступна для Вашей версии R из других источников, см. возможные варианты на https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages) Warning in install.packages : Perhaps you meant ‘FSelector’ ? > install.packages(‘Fselector [2]’) WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:

https://cran.rstudio.com/bin/windows/Rtools/ Устанавливаю пакет в ‘C:/Users/Евдик/AppData/Local/R/win-library/4.4’ (потому что ‘lib’ не определено) Warning in install.packages : пакет ‘‘Fselector [2]’’ недоступен (for this version of R

Другая версия этого пакета может быть доступна для Вашей версии R из других источников, см. возможные варианты на https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages) > install.packages(‘fselector’) WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:

https://cran.rstudio.com/bin/windows/Rtools/ Устанавливаю пакет в ‘C:/Users/Евдик/AppData/Local/R/win-library/4.4’ (потому что ‘lib’ не определено) Warning in install.packages : пакет ‘‘fselector’’ недоступен (for this version of R

Другая версия этого пакета может быть доступна для Вашей версии R из других источников, см. возможные варианты на https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages) Warning in install.packages : Perhaps you meant ‘FSelector’ ? > install.packages(‘FSelector’) WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:

https://cran.rstudio.com/bin/windows/Rtools/ Устанавливаю пакет в ‘C:/Users/Евдик/AppData/Local/R/win-library/4.4’ (потому что ‘lib’ не определено) устанавливаю также зависимости ‘RWekajars’, ‘rJava’, ‘entropy’, ‘randomForest’, ‘RWeka’

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/RWekajars_3.9.3-2.zip’ Content type ‘application/zip’ length 10032953 bytes (9.6 MB) downloaded 9.6 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/rJava_1.0-11.zip’ Content type ‘application/zip’ length 835913 bytes (816 KB) downloaded 816 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/entropy_1.3.1.zip’ Content type ‘application/zip’ length 92701 bytes (90 KB) downloaded 90 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/randomForest_4.7-1.2.zip’ Content type ‘application/zip’ length 225980 bytes (220 KB) downloaded 220 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/RWeka_0.4-46.zip’ Content type ‘application/zip’ length 542018 bytes (529 KB) downloaded 529 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/FSelector_0.34.zip’ Content type ‘application/zip’ length 96292 bytes (94 KB) downloaded 94 KB

пакет ‘RWekajars’ успешно распакован, MD5-суммы проверены пакет ‘rJava’ успешно распакован, MD5-суммы проверены пакет ‘entropy’ успешно распакован, MD5-суммы проверены пакет ‘randomForest’ успешно распакован, MD5-суммы проверены пакет ‘RWeka’ успешно распакован, MD5-суммы проверены пакет ‘FSelector’ успешно распакован, MD5-суммы проверены

Скачанные бинарные пакеты находятся в C:_packages > data(iris) > names(getModelInfo(FSelector)) Ошибка: объект ‘FSelector’ не найден > names(FSelector) Ошибка: объект ‘FSelector’ не найден > names(getModelInfo()) [1] “ada” “AdaBag” “AdaBoost.M1”
[4] “adaboost” “amdai” “ANFIS”
[7] “avNNet” “awnb” “awtan”
[10] “bag” “bagEarth” “bagEarthGCV”
[13] “bagFDA” “bagFDAGCV” “bam”
[16] “bartMachine” “bayesglm” “binda”
[19] “blackboost” “blasso” “blassoAveraged”
[22] “bridge” “brnn” “BstLm”
[25] “bstSm” “bstTree” “C5.0”
[28] “C5.0Cost” “C5.0Rules” “C5.0Tree”
[31] “cforest” “chaid” “CSimca”
[34] “ctree” “ctree2” “cubist”
[37] “dda” “deepboost” “DENFIS”
[40] “dnn” “dwdLinear” “dwdPoly”
[43] “dwdRadial” “earth” “elm”
[46] “enet” “evtree” “extraTrees”
[49] “fda” “FH.GBML” “FIR.DM”
[52] “foba” “FRBCS.CHI” “FRBCS.W”
[55] “FS.HGD” “gam” “gamboost”
[58] “gamLoess” “gamSpline” “gaussprLinear”
[61] “gaussprPoly” “gaussprRadial” “gbm_h2o”
[64] “gbm” “gcvEarth” “GFS.FR.MOGUL”
[67] “GFS.LT.RS” “GFS.THRIFT” “glm.nb”
[70] “glm” “glmboost” “glmnet_h2o”
[73] “glmnet” “glmStepAIC” “gpls”
[76] “hda” “hdda” “hdrda”
[79] “HYFIS” “icr” “J48”
[82] “JRip” “kernelpls” “kknn”
[85] “knn” “krlsPoly” “krlsRadial”
[88] “lars” “lars2” “lasso”
[91] “lda” “lda2” “leapBackward”
[94] “leapForward” “leapSeq” “Linda”
[97] “lm” “lmStepAIC” “LMT”
[100] “loclda” “logicBag” “LogitBoost”
[103] “logreg” “lssvmLinear” “lssvmPoly”
[106] “lssvmRadial” “lvq” “M5”
[109] “M5Rules” “manb” “mda”
[112] “Mlda” “mlp” “mlpKerasDecay”
[115] “mlpKerasDecayCost” “mlpKerasDropout” “mlpKerasDropoutCost” [118] “mlpML” “mlpSGD” “mlpWeightDecay”
[121] “mlpWeightDecayML” “monmlp” “msaenet”
[124] “multinom” “mxnet” “mxnetAdam”
[127] “naive_bayes” “nb” “nbDiscrete”
[130] “nbSearch” “neuralnet” “nnet”
[133] “nnls” “nodeHarvest” “null”
[136] “OneR” “ordinalNet” “ordinalRF”
[139] “ORFlog” “ORFpls” “ORFridge”
[142] “ORFsvm” “ownn” “pam”
[145] “parRF” “PART” “partDSA”
[148] “pcaNNet” “pcr” “pda”
[151] “pda2” “penalized” “PenalizedLDA”
[154] “plr” “pls” “plsRglm”
[157] “polr” “ppr” “pre”
[160] “PRIM” “protoclass” “qda”
[163] “QdaCov” “qrf” “qrnn”
[166] “randomGLM” “ranger” “rbf”
[169] “rbfDDA” “Rborist” “rda”
[172] “regLogistic” “relaxo” “rf”
[175] “rFerns” “RFlda” “rfRules”
[178] “ridge” “rlda” “rlm”
[181] “rmda” “rocc” “rotationForest”
[184] “rotationForestCp” “rpart” “rpart1SE”
[187] “rpart2” “rpartCost” “rpartScore”
[190] “rqlasso” “rqnc” “RRF”
[193] “RRFglobal” “rrlda” “RSimca”
[196] “rvmLinear” “rvmPoly” “rvmRadial”
[199] “SBC” “sda” “sdwd”
[202] “simpls” “SLAVE” “slda”
[205] “smda” “snn” “sparseLDA”
[208] “spikeslab” “spls” “stepLDA”
[211] “stepQDA” “superpc” “svmBoundrangeString” [214] “svmExpoString” “svmLinear” “svmLinear2”
[217] “svmLinear3” “svmLinearWeights” “svmLinearWeights2”
[220] “svmPoly” “svmRadial” “svmRadialCost”
[223] “svmRadialSigma” “svmRadialWeights” “svmSpectrumString”
[226] “tan” “tanSearch” “treebag”
[229] “vbmpRadial” “vglmAdjCat” “vglmContRatio”
[232] “vglmCumulative” “widekernelpls” “WM”
[235] “wsrf” “xgbDART” “xgbLinear”
[238] “xgbTree” “xyf”
> lsf.str(“package:caTools”) Ошибка в as.environment(pos) : в списке поиска нет пункта по имени “package:caTools” > ls(“package:caTools”) Ошибка в as.environment(pos) : в списке поиска нет пункта по имени “package:caTools” > ls(“package:FSelector”) Ошибка в as.environment(pos) : в списке поиска нет пункта по имени “package:FSelector” > weights <- information.gain(Species ~ ., iris) Ошибка в information.gain(Species ~ ., iris) : не могу найти функцию “information.gain” > data(iris) > force(iris) Sepal.Length Sepal.Width Petal.Length Petal.Width Species 1 5.1 3.5 1.4 0.2 setosa 2 4.9 3.0 1.4 0.2 setosa 3 4.7 3.2 1.3 0.2 setosa 4 4.6 3.1 1.5 0.2 setosa 5 5.0 3.6 1.4 0.2 setosa 6 5.4 3.9 1.7 0.4 setosa 7 4.6 3.4 1.4 0.3 setosa 8 5.0 3.4 1.5 0.2 setosa 9 4.4 2.9 1.4 0.2 setosa 10 4.9 3.1 1.5 0.1 setosa 11 5.4 3.7 1.5 0.2 setosa 12 4.8 3.4 1.6 0.2 setosa 13 4.8 3.0 1.4 0.1 setosa 14 4.3 3.0 1.1 0.1 setosa 15 5.8 4.0 1.2 0.2 setosa 16 5.7 4.4 1.5 0.4 setosa 17 5.4 3.9 1.3 0.4 setosa 18 5.1 3.5 1.4 0.3 setosa 19 5.7 3.8 1.7 0.3 setosa 20 5.1 3.8 1.5 0.3 setosa 21 5.4 3.4 1.7 0.2 setosa 22 5.1 3.7 1.5 0.4 setosa 23 4.6 3.6 1.0 0.2 setosa 24 5.1 3.3 1.7 0.5 setosa 25 4.8 3.4 1.9 0.2 setosa 26 5.0 3.0 1.6 0.2 setosa 27 5.0 3.4 1.6 0.4 setosa 28 5.2 3.5 1.5 0.2 setosa 29 5.2 3.4 1.4 0.2 setosa 30 4.7 3.2 1.6 0.2 setosa 31 4.8 3.1 1.6 0.2 setosa 32 5.4 3.4 1.5 0.4 setosa 33 5.2 4.1 1.5 0.1 setosa 34 5.5 4.2 1.4 0.2 setosa 35 4.9 3.1 1.5 0.2 setosa 36 5.0 3.2 1.2 0.2 setosa 37 5.5 3.5 1.3 0.2 setosa 38 4.9 3.6 1.4 0.1 setosa 39 4.4 3.0 1.3 0.2 setosa 40 5.1 3.4 1.5 0.2 setosa 41 5.0 3.5 1.3 0.3 setosa 42 4.5 2.3 1.3 0.3 setosa 43 4.4 3.2 1.3 0.2 setosa 44 5.0 3.5 1.6 0.6 setosa 45 5.1 3.8 1.9 0.4 setosa 46 4.8 3.0 1.4 0.3 setosa 47 5.1 3.8 1.6 0.2 setosa 48 4.6 3.2 1.4 0.2 setosa 49 5.3 3.7 1.5 0.2 setosa 50 5.0 3.3 1.4 0.2 setosa 51 7.0 3.2 4.7 1.4 versicolor 52 6.4 3.2 4.5 1.5 versicolor 53 6.9 3.1 4.9 1.5 versicolor 54 5.5 2.3 4.0 1.3 versicolor 55 6.5 2.8 4.6 1.5 versicolor 56 5.7 2.8 4.5 1.3 versicolor 57 6.3 3.3 4.7 1.6 versicolor 58 4.9 2.4 3.3 1.0 versicolor 59 6.6 2.9 4.6 1.3 versicolor 60 5.2 2.7 3.9 1.4 versicolor 61 5.0 2.0 3.5 1.0 versicolor 62 5.9 3.0 4.2 1.5 versicolor 63 6.0 2.2 4.0 1.0 versicolor 64 6.1 2.9 4.7 1.4 versicolor 65 5.6 2.9 3.6 1.3 versicolor 66 6.7 3.1 4.4 1.4 versicolor 67 5.6 3.0 4.5 1.5 versicolor 68 5.8 2.7 4.1 1.0 versicolor 69 6.2 2.2 4.5 1.5 versicolor 70 5.6 2.5 3.9 1.1 versicolor 71 5.9 3.2 4.8 1.8 versicolor 72 6.1 2.8 4.0 1.3 versicolor 73 6.3 2.5 4.9 1.5 versicolor 74 6.1 2.8 4.7 1.2 versicolor 75 6.4 2.9 4.3 1.3 versicolor 76 6.6 3.0 4.4 1.4 versicolor 77 6.8 2.8 4.8 1.4 versicolor 78 6.7 3.0 5.0 1.7 versicolor 79 6.0 2.9 4.5 1.5 versicolor 80 5.7 2.6 3.5 1.0 versicolor 81 5.5 2.4 3.8 1.1 versicolor 82 5.5 2.4 3.7 1.0 versicolor 83 5.8 2.7 3.9 1.2 versicolor 84 6.0 2.7 5.1 1.6 versicolor 85 5.4 3.0 4.5 1.5 versicolor 86 6.0 3.4 4.5 1.6 versicolor 87 6.7 3.1 4.7 1.5 versicolor 88 6.3 2.3 4.4 1.3 versicolor 89 5.6 3.0 4.1 1.3 versicolor 90 5.5 2.5 4.0 1.3 versicolor 91 5.5 2.6 4.4 1.2 versicolor 92 6.1 3.0 4.6 1.4 versicolor 93 5.8 2.6 4.0 1.2 versicolor 94 5.0 2.3 3.3 1.0 versicolor 95 5.6 2.7 4.2 1.3 versicolor 96 5.7 3.0 4.2 1.2 versicolor 97 5.7 2.9 4.2 1.3 versicolor 98 6.2 2.9 4.3 1.3 versicolor 99 5.1 2.5 3.0 1.1 versicolor 100 5.7 2.8 4.1 1.3 versicolor 101 6.3 3.3 6.0 2.5 virginica 102 5.8 2.7 5.1 1.9 virginica 103 7.1 3.0 5.9 2.1 virginica 104 6.3 2.9 5.6 1.8 virginica 105 6.5 3.0 5.8 2.2 virginica 106 7.6 3.0 6.6 2.1 virginica 107 4.9 2.5 4.5 1.7 virginica 108 7.3 2.9 6.3 1.8 virginica 109 6.7 2.5 5.8 1.8 virginica 110 7.2 3.6 6.1 2.5 virginica 111 6.5 3.2 5.1 2.0 virginica 112 6.4 2.7 5.3 1.9 virginica 113 6.8 3.0 5.5 2.1 virginica 114 5.7 2.5 5.0 2.0 virginica 115 5.8 2.8 5.1 2.4 virginica 116 6.4 3.2 5.3 2.3 virginica 117 6.5 3.0 5.5 1.8 virginica 118 7.7 3.8 6.7 2.2 virginica 119 7.7 2.6 6.9 2.3 virginica 120 6.0 2.2 5.0 1.5 virginica 121 6.9 3.2 5.7 2.3 virginica 122 5.6 2.8 4.9 2.0 virginica 123 7.7 2.8 6.7 2.0 virginica 124 6.3 2.7 4.9 1.8 virginica 125 6.7 3.3 5.7 2.1 virginica 126 7.2 3.2 6.0 1.8 virginica 127 6.2 2.8 4.8 1.8 virginica 128 6.1 3.0 4.9 1.8 virginica 129 6.4 2.8 5.6 2.1 virginica 130 7.2 3.0 5.8 1.6 virginica 131 7.4 2.8 6.1 1.9 virginica 132 7.9 3.8 6.4 2.0 virginica 133 6.4 2.8 5.6 2.2 virginica 134 6.3 2.8 5.1 1.5 virginica 135 6.1 2.6 5.6 1.4 virginica 136 7.7 3.0 6.1 2.3 virginica 137 6.3 3.4 5.6 2.4 virginica 138 6.4 3.1 5.5 1.8 virginica 139 6.0 3.0 4.8 1.8 virginica 140 6.9 3.1 5.4 2.1 virginica 141 6.7 3.1 5.6 2.4 virginica 142 6.9 3.1 5.1 2.3 virginica 143 5.8 2.7 5.1 1.9 virginica 144 6.8 3.2 5.9 2.3 virginica 145 6.7 3.3 5.7 2.5 virginica 146 6.7 3.0 5.2 2.3 virginica 147 6.3 2.5 5.0 1.9 virginica 148 6.5 3.0 5.2 2.0 virginica 149 6.2 3.4 5.4 2.3 virginica 150 5.9 3.0 5.1 1.8 virginica > weights <- information.gain(Species ~ ., iris) Ошибка в information.gain(Species ~ ., iris) : не могу найти функцию “information.gain” > information.gain(Species ~ ., iris) Ошибка в information.gain(Species ~ ., iris) : не могу найти функцию “information.gain” > install.packages(‘FSelectorRcpp’) WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:

https://cran.rstudio.com/bin/windows/Rtools/ Устанавливаю пакет в ‘C:/Users/Евдик/AppData/Local/R/win-library/4.4’ (потому что ‘lib’ не определено) устанавливаю также зависимости ‘BH’, ‘RcppArmadillo’

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/BH_1.87.0-1.zip’ Content type ‘application/zip’ length 21797583 bytes (20.8 MB) downloaded 20.8 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/RcppArmadillo_14.4.0-1.zip’ Content type ‘application/zip’ length 2062809 bytes (2.0 MB) downloaded 2.0 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/FSelectorRcpp_0.3.13.zip’ Content type ‘application/zip’ length 770077 bytes (752 KB) downloaded 752 KB

пакет ‘BH’ успешно распакован, MD5-суммы проверены пакет ‘RcppArmadillo’ успешно распакован, MD5-суммы проверены пакет ‘FSelectorRcpp’ успешно распакован, MD5-суммы проверены

Скачанные бинарные пакеты находятся в C:_packages > weights <- information.gain(Species ~ ., iris) Ошибка в information.gain(Species ~ ., iris) : не могу найти функцию “information.gain” > library(FSelectorRcpp) Предупреждение: пакет ‘FSelectorRcpp’ был собран под R версии 4.4.3 > weights <- information.gain(Species ~ ., iris) Ошибка в information.gain(Species ~ ., iris) : не могу найти функцию “information.gain” > information.gain(Species ~ ., iris) Ошибка в information.gain(Species ~ ., iris) : не могу найти функцию “information.gain” > library(FSelector) Ошибка: не удалась загрузка пакета или пространства имен для ‘FSelector’: .onLoad не удалось в loadNamespace() для ‘RWekajars’, подробности: вызов: .jinit(parameters = parameters) ошибка: Unable to create a Java class loader. Вдобавок: Предупреждение: пакет ‘FSelector’ был собран под R версии 4.4.3 > information.gain(Species ~ ., iris)ъ Ошибка: неожиданный символ в “information.gain(Species ~ ., iris)ъ” > information.gain(Species ~ ., iris) Ошибка в information.gain(Species ~ ., iris) : не могу найти функцию “information.gain” > weights <- information_gain(Species ~ ., iris) > print(weights) attributes importance 1 Sepal.Length 0.4521286 2 Sepal.Width 0.2672750 3 Petal.Length 0.9402853 4 Petal.Width 0.9554360 > > install.packages(“arules”) WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:

https://cran.rstudio.com/bin/windows/Rtools/ Устанавливаю пакет в ‘C:/Users/Евдик/AppData/Local/R/win-library/4.4’ (потому что ‘lib’ не определено) пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/arules_1.7-9.zip’ Content type ‘application/zip’ length 2631138 bytes (2.5 MB) downloaded 2.5 MB

пакет ‘arules’ успешно распакован, MD5-суммы проверены

Скачанные бинарные пакеты находятся в C:_packages > library(arules) Загрузка требуемого пакета: Matrix

Присоединяю пакет: ‘arules’

Следующий объект скрыт от ‘package:FSelectorRcpp’:

discretize

Следующие объекты скрыты от ‘package:base’:

abbreviate, write

Предупреждение: пакет ‘arules’ был собран под R версии 4.4.3 > iris\(Sepal.Length_interval <- discretize(iris\)Sepal.Length, method = “interval”, breaks = 3) > iris\(Sepal.Length_frequency <- discretize(iris\)Sepal.Length, method = “frequency”, breaks = 3) > iris\(Sepal.Length_cluster <- discretize(iris\)Sepal.Length, method = “cluster”, breaks = 3) > iris\(Sepal.Length_fixed <- discretize(iris\)Sepal.Length, method = “fixed”, breaks = c(-Inf, 5, 6, Inf)) > View(iris) > iris\(Sepal.Length_interval [1] [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [9] [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [5.5,6.7) [5.5,6.7) [17] [4.3,5.5) [4.3,5.5) [5.5,6.7) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [25] [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [33] [4.3,5.5) [5.5,6.7) [4.3,5.5) [4.3,5.5) [5.5,6.7) [4.3,5.5) [4.3,5.5) [4.3,5.5) [41] [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [4.3,5.5) [49] [4.3,5.5) [4.3,5.5) [6.7,7.9] [5.5,6.7) [6.7,7.9] [5.5,6.7) [5.5,6.7) [5.5,6.7) [57] [5.5,6.7) [4.3,5.5) [5.5,6.7) [4.3,5.5) [4.3,5.5) [5.5,6.7) [5.5,6.7) [5.5,6.7) [65] [5.5,6.7) [6.7,7.9] [5.5,6.7) [5.5,6.7) [5.5,6.7) [5.5,6.7) [5.5,6.7) [5.5,6.7) [73] [5.5,6.7) [5.5,6.7) [5.5,6.7) [5.5,6.7) [6.7,7.9] [6.7,7.9] [5.5,6.7) [5.5,6.7) [81] [5.5,6.7) [5.5,6.7) [5.5,6.7) [5.5,6.7) [4.3,5.5) [5.5,6.7) [6.7,7.9] [5.5,6.7) [89] [5.5,6.7) [5.5,6.7) [5.5,6.7) [5.5,6.7) [5.5,6.7) [4.3,5.5) [5.5,6.7) [5.5,6.7) [97] [5.5,6.7) [5.5,6.7) [4.3,5.5) [5.5,6.7) [5.5,6.7) [5.5,6.7) [6.7,7.9] [5.5,6.7) [105] [5.5,6.7) [6.7,7.9] [4.3,5.5) [6.7,7.9] [6.7,7.9] [6.7,7.9] [5.5,6.7) [5.5,6.7) [113] [6.7,7.9] [5.5,6.7) [5.5,6.7) [5.5,6.7) [5.5,6.7) [6.7,7.9] [6.7,7.9] [5.5,6.7) [121] [6.7,7.9] [5.5,6.7) [6.7,7.9] [5.5,6.7) [6.7,7.9] [6.7,7.9] [5.5,6.7) [5.5,6.7) [129] [5.5,6.7) [6.7,7.9] [6.7,7.9] [6.7,7.9] [5.5,6.7) [5.5,6.7) [5.5,6.7) [6.7,7.9] [137] [5.5,6.7) [5.5,6.7) [5.5,6.7) [6.7,7.9] [6.7,7.9] [6.7,7.9] [5.5,6.7) [6.7,7.9] [145] [6.7,7.9] [6.7,7.9] [5.5,6.7) [5.5,6.7) [5.5,6.7) [5.5,6.7) attr(,"discretized:breaks") [1] 4.3 5.5 6.7 7.9 attr(,"discretized:method") [1] interval Levels: [4.3,5.5) [5.5,6.7) [6.7,7.9] > iris\)Sepal.Length_frequency [1] [4.3,5.4) [4.3,5.4) [4.3,5.4) [4.3,5.4) [4.3,5.4) [5.4,6.3) [4.3,5.4) [4.3,5.4) [9] [4.3,5.4) [4.3,5.4) [5.4,6.3) [4.3,5.4) [4.3,5.4) [4.3,5.4) [5.4,6.3) [5.4,6.3) [17] [5.4,6.3) [4.3,5.4) [5.4,6.3) [4.3,5.4) [5.4,6.3) [4.3,5.4) [4.3,5.4) [4.3,5.4) [25] [4.3,5.4) [4.3,5.4) [4.3,5.4) [4.3,5.4) [4.3,5.4) [4.3,5.4) [4.3,5.4) [5.4,6.3) [33] [4.3,5.4) [5.4,6.3) [4.3,5.4) [4.3,5.4) [5.4,6.3) [4.3,5.4) [4.3,5.4) [4.3,5.4) [41] [4.3,5.4) [4.3,5.4) [4.3,5.4) [4.3,5.4) [4.3,5.4) [4.3,5.4) [4.3,5.4) [4.3,5.4) [49] [4.3,5.4) [4.3,5.4) [6.3,7.9] [6.3,7.9] [6.3,7.9] [5.4,6.3) [6.3,7.9] [5.4,6.3) [57] [6.3,7.9] [4.3,5.4) [6.3,7.9] [4.3,5.4) [4.3,5.4) [5.4,6.3) [5.4,6.3) [5.4,6.3) [65] [5.4,6.3) [6.3,7.9] [5.4,6.3) [5.4,6.3) [5.4,6.3) [5.4,6.3) [5.4,6.3) [5.4,6.3) [73] [6.3,7.9] [5.4,6.3) [6.3,7.9] [6.3,7.9] [6.3,7.9] [6.3,7.9] [5.4,6.3) [5.4,6.3) [81] [5.4,6.3) [5.4,6.3) [5.4,6.3) [5.4,6.3) [5.4,6.3) [5.4,6.3) [6.3,7.9] [6.3,7.9] [89] [5.4,6.3) [5.4,6.3) [5.4,6.3) [5.4,6.3) [5.4,6.3) [4.3,5.4) [5.4,6.3) [5.4,6.3) [97] [5.4,6.3) [5.4,6.3) [4.3,5.4) [5.4,6.3) [6.3,7.9] [5.4,6.3) [6.3,7.9] [6.3,7.9] [105] [6.3,7.9] [6.3,7.9] [4.3,5.4) [6.3,7.9] [6.3,7.9] [6.3,7.9] [6.3,7.9] [6.3,7.9] [113] [6.3,7.9] [5.4,6.3) [5.4,6.3) [6.3,7.9] [6.3,7.9] [6.3,7.9] [6.3,7.9] [5.4,6.3) [121] [6.3,7.9] [5.4,6.3) [6.3,7.9] [6.3,7.9] [6.3,7.9] [6.3,7.9] [5.4,6.3) [5.4,6.3) [129] [6.3,7.9] [6.3,7.9] [6.3,7.9] [6.3,7.9] [6.3,7.9] [6.3,7.9] [5.4,6.3) [6.3,7.9] [137] [6.3,7.9] [6.3,7.9] [5.4,6.3) [6.3,7.9] [6.3,7.9] [6.3,7.9] [5.4,6.3) [6.3,7.9] [145] [6.3,7.9] [6.3,7.9] [6.3,7.9] [6.3,7.9] [5.4,6.3) [5.4,6.3) attr(,“discretized:breaks”) [1] 4.3 5.4 6.3 7.9 attr(,“discretized:method”) [1] frequency Levels: [4.3,5.4) [5.4,6.3) [6.3,7.9] > iris\(Sepal.Length_cluster [1] [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [8] [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [15] [5.42,6.39) [5.42,6.39) [4.3,5.42) [4.3,5.42) [5.42,6.39) [4.3,5.42) [4.3,5.42) [22] [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [29] [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [5.42,6.39) [4.3,5.42) [36] [4.3,5.42) [5.42,6.39) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [43] [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [4.3,5.42) [50] [4.3,5.42) [6.39,7.9] [6.39,7.9] [6.39,7.9] [5.42,6.39) [6.39,7.9] [5.42,6.39) [57] [5.42,6.39) [4.3,5.42) [6.39,7.9] [4.3,5.42) [4.3,5.42) [5.42,6.39) [5.42,6.39) [64] [5.42,6.39) [5.42,6.39) [6.39,7.9] [5.42,6.39) [5.42,6.39) [5.42,6.39) [5.42,6.39) [71] [5.42,6.39) [5.42,6.39) [5.42,6.39) [5.42,6.39) [6.39,7.9] [6.39,7.9] [6.39,7.9] [78] [6.39,7.9] [5.42,6.39) [5.42,6.39) [5.42,6.39) [5.42,6.39) [5.42,6.39) [5.42,6.39) [85] [4.3,5.42) [5.42,6.39) [6.39,7.9] [5.42,6.39) [5.42,6.39) [5.42,6.39) [5.42,6.39) [92] [5.42,6.39) [5.42,6.39) [4.3,5.42) [5.42,6.39) [5.42,6.39) [5.42,6.39) [5.42,6.39) [99] [4.3,5.42) [5.42,6.39) [5.42,6.39) [5.42,6.39) [6.39,7.9] [5.42,6.39) [6.39,7.9] [106] [6.39,7.9] [4.3,5.42) [6.39,7.9] [6.39,7.9] [6.39,7.9] [6.39,7.9] [6.39,7.9] [113] [6.39,7.9] [5.42,6.39) [5.42,6.39) [6.39,7.9] [6.39,7.9] [6.39,7.9] [6.39,7.9] [120] [5.42,6.39) [6.39,7.9] [5.42,6.39) [6.39,7.9] [5.42,6.39) [6.39,7.9] [6.39,7.9] [127] [5.42,6.39) [5.42,6.39) [6.39,7.9] [6.39,7.9] [6.39,7.9] [6.39,7.9] [6.39,7.9] [134] [5.42,6.39) [5.42,6.39) [6.39,7.9] [5.42,6.39) [6.39,7.9] [5.42,6.39) [6.39,7.9] [141] [6.39,7.9] [6.39,7.9] [5.42,6.39) [6.39,7.9] [6.39,7.9] [6.39,7.9] [5.42,6.39) [148] [6.39,7.9] [5.42,6.39) [5.42,6.39) attr(,"discretized:breaks") [1] 4.300000 5.424245 6.385417 7.900000 attr(,"discretized:method") [1] cluster Levels: [4.3,5.42) [5.42,6.39) [6.39,7.9] > iris\)Sepal.Length_fixed [1] [5,6) [-Inf,5) [-Inf,5) [-Inf,5) [5,6) [5,6) [-Inf,5) [5,6) [-Inf,5) [10] [-Inf,5) [5,6) [-Inf,5) [-Inf,5) [-Inf,5) [5,6) [5,6) [5,6) [5,6)
[19] [5,6) [5,6) [5,6) [5,6) [-Inf,5) [5,6) [-Inf,5) [5,6) [5,6)
[28] [5,6) [5,6) [-Inf,5) [-Inf,5) [5,6) [5,6) [5,6) [-Inf,5) [5,6)
[37] [5,6) [-Inf,5) [-Inf,5) [5,6) [5,6) [-Inf,5) [-Inf,5) [5,6) [5,6)
[46] [-Inf,5) [5,6) [-Inf,5) [5,6) [5,6) [6, Inf] [6, Inf] [6, Inf] [5,6)
[55] [6, Inf] [5,6) [6, Inf] [-Inf,5) [6, Inf] [5,6) [5,6) [5,6) [6, Inf] [64] [6, Inf] [5,6) [6, Inf] [5,6) [5,6) [6, Inf] [5,6) [5,6) [6, Inf] [73] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [5,6) [5,6)
[82] [5,6) [5,6) [6, Inf] [5,6) [6, Inf] [6, Inf] [6, Inf] [5,6) [5,6)
[91] [5,6) [6, Inf] [5,6) [5,6) [5,6) [5,6) [5,6) [6, Inf] [5,6)
[100] [5,6) [6, Inf] [5,6) [6, Inf] [6, Inf] [6, Inf] [6, Inf] [-Inf,5) [6, Inf] [109] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [5,6) [5,6) [6, Inf] [6, Inf] [118] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [5,6) [6, Inf] [6, Inf] [6, Inf] [6, Inf] [127] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [136] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [5,6) [6, Inf] [145] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [6, Inf] [5,6)
attr(,“discretized:breaks”) [1] -Inf 5 6 Inf attr(,“discretized:method”) [1] fixed Levels: [-Inf,5) [5,6) [6, Inf] > install.packages(“Boruta”) WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:

https://cran.rstudio.com/bin/windows/Rtools/ Устанавливаю пакет в ‘C:/Users/Евдик/AppData/Local/R/win-library/4.4’ (потому что ‘lib’ не определено) устанавливаю также зависимости ‘RcppEigen’, ‘ranger’

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/RcppEigen_0.3.4.0.2.zip’ Content type ‘application/zip’ length 2592462 bytes (2.5 MB) downloaded 2.5 MB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/ranger_0.17.0.zip’ Content type ‘application/zip’ length 799205 bytes (780 KB) downloaded 780 KB

пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/Boruta_8.0.0.zip’ Content type ‘application/zip’ length 457960 bytes (447 KB) downloaded 447 KB

пакет ‘RcppEigen’ успешно распакован, MD5-суммы проверены пакет ‘ranger’ успешно распакован, MD5-суммы проверены пакет ‘Boruta’ успешно распакован, MD5-суммы проверены

Скачанные бинарные пакеты находятся в C:_packages > library(Boruta) Предупреждение: пакет ‘Boruta’ был собран под R версии 4.4.3 > data(“Ozone”) Предупреждение: В data(“Ozone”) : данные ‘Ozone’ не найдены > install.packages(“mlbench”) WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:

https://cran.rstudio.com/bin/windows/Rtools/ Устанавливаю пакет в ‘C:/Users/Евдик/AppData/Local/R/win-library/4.4’ (потому что ‘lib’ не определено) пробую URL ‘https://cran.rstudio.com/bin/windows/contrib/4.4/mlbench_2.1-6.zip’ Content type ‘application/zip’ length 1062170 bytes (1.0 MB) downloaded 1.0 MB

пакет ‘mlbench’ успешно распакован, MD5-суммы проверены

Скачанные бинарные пакеты находятся в C:_packages > library(mlbench) Предупреждение: пакет ‘mlbench’ был собран под R версии 4.4.3 > data(“Ozone”) > boruta_output <- Boruta(Ozone ~ ., data = Ozone, doTrace = 2) 1. run of importance source… Ошибка: Error: Missing data in dependent variable. > plot(boruta_output, cex.axis = 0.7, las = 2, xlab = ““, main =”Важность признаков”) Ошибка: объект ‘boruta_output’ не найден > boruta_output <- Boruta(V4 ~ ., data = Ozone_clean, doTrace = 2) Ошибка: объект ‘Ozone_clean’ не найден > sum(is.na(Ozone\(V4)) [1] 5 > Ozone_clean <- na.omit(Ozone) > sum(is.na(Ozone_clean\)V4)) [1] 0 > boruta_output <- Boruta(V4 ~ ., data = Ozone_clean, doTrace = 2) 1. run of importance source… 2. run of importance source… 3. run of importance source… 4. run of importance source… 5. run of importance source… 6. run of importance source… 7. run of importance source… 8. run of importance source… 9. run of importance source… 10. run of importance source… 11. run of importance source… After 11 iterations, +0.71 secs: confirmed 9 attributes: V1, V10, V11, V12, V13 and 4 more; rejected 2 attributes: V2, V3; still have 1 attribute left.

  1. run of importance source…
  2. run of importance source…
  3. run of importance source…
  4. run of importance source…
  5. run of importance source…
  6. run of importance source…
  7. run of importance source…
  8. run of importance source…
  9. run of importance source…
  10. run of importance source…
  11. run of importance source…
  12. run of importance source…
  13. run of importance source…
  14. run of importance source…
  15. run of importance source…
  16. run of importance source… After 27 iterations, +1.6 secs: rejected 1 attribute: V6; no more attributes left.

print(boruta_output) Boruta performed 27 iterations in 1.64822 secs. 9 attributes confirmed important: V1, V10, V11, V12, V13 and 4 more; 3 attributes confirmed unimportant: V2, V3, V6; boruta_output <- Boruta(Ozone ~ ., data = Ozone, doTrace = 2) 1. run of importance source… Ошибка: Error: Missing data in dependent variable. plot(boruta_output, cex.axis = 0.7, las = 2, xlab = ““, main =”Важность признаков”) boxplot(boruta_output, cex.axis = 0.7, las = 2, xlab = ““, main =”Важность признаков”) Ошибка в sort.int(x, na.last = na.last, decreasing = decreasing, …) : ‘x’ должен быть элементарным Вдобавок: Предупреждения: 1: В is.na(x) : is.na() применен к не-списку/вектору типа ‘language’ 2: В is.na(x) : is.na() применен к не-списку/вектору типа ‘language’ importance <- attStats(boruta_output) importance_df <- as.data.frame(importance) boxplot(importance_df$meanImp, + main = “Важность признаков”, + xlab = “Признаки”, + ylab = “Средняя важность”, + col = “lightblue”)