The whole code is as follows: library(caret) library(farff) library(gbm) library(nnet) setwd("C:/Users/PC/Documents") d=readARFF("myresults.arff") index <- createDataPartition(d$results, p = .70,list = FALSE) tr <- d[index, ] ts <- d[-index, ] index_2 <- createFolds(tr$results, returnTrain = TRUE, list = TRUE) ctrl <- trainControl(method = "repeatedcv", index = index_2) set.seed(30218) nnet1 <- train(results~ ., data = tr, method = "nnet", metric = "MAE", trControl = ctrl, preProc = c("center", "scale", "zv"), tuneGrid = data.frame(decay = (1), size = (1.3801517))) nnet1$results ///For SVM set.seed(30218) svm1 <- train(results ~ ., data = tr, method = "svmRadial", metric = "MAE", preProc = c("center", "scale", "zv"), trControl = ctrl, tuneGrid=expand.grid(sigma = (0.5), C = c(1.348657))) getTrainPerf(svm1) svm1$results //For GBM set.seed(30218) gbm <- train(results ~ ., data = tr, method = "gbm", preProc = c("center", "scale", "zv"), metric = "MAE", tuneGrid = data.frame(n.trees = (200.09633523), interaction.depth = (1), shrinkage=(0.1), n.minobsinnode=(10))) gbm$results //Then the boxplot rvalues=resamples(list(nnet=nnet1, svm=svm1, GBM=gbm)) bwplot(rvalues, metric="MAE") On Fri, Feb 21, 2020 at 12:16 AM Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote:> You are being way too cavalier about what packages you are using. Read the > Posting Guide about contributed packages... this list cannot provide expert > support for every package out there. This confusion is why you should be > providing a reproducible example when you ask for help about R. > > The caret package depends on lattice and provides some overloaded versions > of the bwplot function that do have a metric argument. I have no expertise > with caret myself... but recommend that you supply a reproducible example > for best luck in prompting someone to look closer. > > On February 20, 2020 1:31:30 PM PST, javed khan <javedbtk111 at gmail.com> > wrote: > >Thanks for your reply. > > > >I am not using any specific package for bwplot. I just used caret, nnet > >and > >gbm packages. > > > >When I use resample (instead of resamples), it give me error message. > > > >metric=MAE gives the MAE values at x-axis when I used simple plots in > >the > >recent past. > > > >Best regards > > > >On Thu, Feb 20, 2020 at 10:29 PM Bert Gunter <bgunter.4567 at gmail.com> > >wrote: > > > >> cc the list! > >> (which I have done here) > >> > >> Bert Gunter > >> > >> "The trouble with having an open mind is that people keep coming > >along and > >> sticking things into it." > >> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > >> > >> > >> On Thu, Feb 20, 2020 at 1:20 PM javed khan <javedbtk111 at gmail.com> > >wrote: > >> > >>> Thanks for your reply. > >>> > >>> I am not using any specific package for bwplot. I just used caret, > >nnet > >>> and gbm packages. > >>> > >>> When I use resample (instead of resamples), it give me error > >message. > >>> > >>> metric=MAE gives the MAE values at x-axis when I used simple plots > >in the > >>> recent past. > >>> > >>> Best regards > >>> > >>> On Thu, Feb 20, 2020 at 10:15 PM Bert Gunter > ><bgunter.4567 at gmail.com> > >>> wrote: > >>> > >>>> ?? > >>>> Isn't is resample() not resamples()? > >>>> From what package? > >>>> What package is bwplot from? lattice:::bwplot has no "metric" > >argument. > >>>> > >>>> > >>>> > >>>> Bert Gunter > >>>> > >>>> "The trouble with having an open mind is that people keep coming > >along > >>>> and sticking things into it." > >>>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > >>>> > >>>> > >>>> On Thu, Feb 20, 2020 at 12:55 PM javed khan <javedbtk111 at gmail.com> > >>>> wrote: > >>>> > >>>>> Hello to all > >>>>> > >>>>> I have different train functions for NN, SVM and GBM and when I > >combine > >>>>> the > >>>>> results using bwplot, it gives me the error " Different number of > >>>>> resamples > >>>>> in each model". It gives me the results (MAE values) but using the > >>>>> boxplot, > >>>>> it gives the error. The code is as follows: > >>>>> > >>>>> set.seed(30218) > >>>>> nnet1 <- train(results~ ., data = tr, > >>>>> method = "nnet", > >>>>> > >>>>> metric = "MAE", > >>>>> trControl = ctrl, > >>>>> > >>>>> preProc = c("center", "scale", "zv"), > >>>>> tuneGrid = data.frame(decay = (1), > >>>>> size = (1.3801517))) > >>>>> nnet1$results > >>>>> > >>>>> ///For SVM > >>>>> > >>>>> set.seed(30218) > >>>>> svm1 <- train(results ~ ., data = tr, > >>>>> method = "svmRadial", > >>>>> > >>>>> metric = "MAE", > >>>>> preProc = c("center", "scale", "zv"), > >>>>> trControl = ctrl, > >>>>> tuneGrid=expand.grid(sigma = (0.5), > >>>>> C = c(1.348657))) > >>>>> getTrainPerf(svm1) > >>>>> svm1$results > >>>>> > >>>>> //For GBM > >>>>> > >>>>> set.seed(30218) > >>>>> gbm <- train(results ~ ., data = tr, > >>>>> method = "gbm", > >>>>> preProc = c("center", "scale", "zv"), > >>>>> metric = "MAE", > >>>>> > >>>>> > >>>>> tuneGrid = data.frame(n.trees = (200.09633523), > >>>>> interaction.depth = (1), > >>>>> shrinkage=(0.1), > >>>>> n.minobsinnode=(10))) > >>>>> gbm$results > >>>>> > >>>>> //Then the boxplot > >>>>> > >>>>> rvalues=resamples(list(nnet=nnet1, svm=svm1, GBM=gbm)) > >>>>> > >>>>> bwplot(rvalues, metric="MAE") > >>>>> > >>>>> [[alternative HTML version deleted]] > >>>>> > >>>>> ______________________________________________ > >>>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > >>>>> https://stat.ethz.ch/mailman/listinfo/r-help > >>>>> PLEASE do read the posting guide > >>>>> http://www.R-project.org/posting-guide.html > >>>>> and provide commented, minimal, self-contained, reproducible code. > >>>>> > >>>> > > > > [[alternative HTML version deleted]] > > > >______________________________________________ > >R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > >https://stat.ethz.ch/mailman/listinfo/r-help > >PLEASE do read the posting guide > >http://www.R-project.org/posting-guide.html > >and provide commented, minimal, self-contained, reproducible code. > > -- > Sent from my phone. Please excuse my brevity. >[[alternative HTML version deleted]]
When I do not include gbm in the boxplot, it gives me the result for nnet and svm but when I include also gbm, it gives the error message There are different numbers of resamples in each model On Fri, Feb 21, 2020 at 10:00 AM javed khan <javedbtk111 at gmail.com> wrote:> The whole code is as follows: > > library(caret) > library(farff) > library(gbm) > library(nnet) > > setwd("C:/Users/PC/Documents") > d=readARFF("myresults.arff") > > index <- createDataPartition(d$results, p = .70,list = FALSE) > tr <- d[index, ] > ts <- d[-index, ] > index_2 <- createFolds(tr$results, returnTrain = TRUE, list = TRUE) > ctrl <- trainControl(method = "repeatedcv", index = index_2) > > set.seed(30218) > nnet1 <- train(results~ ., data = tr, > method = "nnet", > > metric = "MAE", > trControl = ctrl, > > preProc = c("center", "scale", "zv"), > tuneGrid = data.frame(decay = (1), > size = (1.3801517))) > nnet1$results > > ///For SVM > > set.seed(30218) > svm1 <- train(results ~ ., data = tr, > method = "svmRadial", > > metric = "MAE", > preProc = c("center", "scale", "zv"), > trControl = ctrl, > tuneGrid=expand.grid(sigma = (0.5), > C = c(1.348657))) > getTrainPerf(svm1) > svm1$results > > //For GBM > > set.seed(30218) > gbm <- train(results ~ ., data = tr, > method = "gbm", > preProc = c("center", "scale", "zv"), > metric = "MAE", > > > tuneGrid = data.frame(n.trees = (200.09633523), > interaction.depth = (1), > shrinkage=(0.1), n.minobsinnode=(10))) > gbm$results > > //Then the boxplot > > rvalues=resamples(list(nnet=nnet1, svm=svm1, GBM=gbm)) > > bwplot(rvalues, metric="MAE") > > > On Fri, Feb 21, 2020 at 12:16 AM Jeff Newmiller <jdnewmil at dcn.davis.ca.us> > wrote: > >> You are being way too cavalier about what packages you are using. Read >> the Posting Guide about contributed packages... this list cannot provide >> expert support for every package out there. This confusion is why you >> should be providing a reproducible example when you ask for help about R. >> >> The caret package depends on lattice and provides some overloaded >> versions of the bwplot function that do have a metric argument. I have no >> expertise with caret myself... but recommend that you supply a reproducible >> example for best luck in prompting someone to look closer. >> >> On February 20, 2020 1:31:30 PM PST, javed khan <javedbtk111 at gmail.com> >> wrote: >> >Thanks for your reply. >> > >> >I am not using any specific package for bwplot. I just used caret, nnet >> >and >> >gbm packages. >> > >> >When I use resample (instead of resamples), it give me error message. >> > >> >metric=MAE gives the MAE values at x-axis when I used simple plots in >> >the >> >recent past. >> > >> >Best regards >> > >> >On Thu, Feb 20, 2020 at 10:29 PM Bert Gunter <bgunter.4567 at gmail.com> >> >wrote: >> > >> >> cc the list! >> >> (which I have done here) >> >> >> >> Bert Gunter >> >> >> >> "The trouble with having an open mind is that people keep coming >> >along and >> >> sticking things into it." >> >> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) >> >> >> >> >> >> On Thu, Feb 20, 2020 at 1:20 PM javed khan <javedbtk111 at gmail.com> >> >wrote: >> >> >> >>> Thanks for your reply. >> >>> >> >>> I am not using any specific package for bwplot. I just used caret, >> >nnet >> >>> and gbm packages. >> >>> >> >>> When I use resample (instead of resamples), it give me error >> >message. >> >>> >> >>> metric=MAE gives the MAE values at x-axis when I used simple plots >> >in the >> >>> recent past. >> >>> >> >>> Best regards >> >>> >> >>> On Thu, Feb 20, 2020 at 10:15 PM Bert Gunter >> ><bgunter.4567 at gmail.com> >> >>> wrote: >> >>> >> >>>> ?? >> >>>> Isn't is resample() not resamples()? >> >>>> From what package? >> >>>> What package is bwplot from? lattice:::bwplot has no "metric" >> >argument. >> >>>> >> >>>> >> >>>> >> >>>> Bert Gunter >> >>>> >> >>>> "The trouble with having an open mind is that people keep coming >> >along >> >>>> and sticking things into it." >> >>>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) >> >>>> >> >>>> >> >>>> On Thu, Feb 20, 2020 at 12:55 PM javed khan <javedbtk111 at gmail.com> >> >>>> wrote: >> >>>> >> >>>>> Hello to all >> >>>>> >> >>>>> I have different train functions for NN, SVM and GBM and when I >> >combine >> >>>>> the >> >>>>> results using bwplot, it gives me the error " Different number of >> >>>>> resamples >> >>>>> in each model". It gives me the results (MAE values) but using the >> >>>>> boxplot, >> >>>>> it gives the error. The code is as follows: >> >>>>> >> >>>>> set.seed(30218) >> >>>>> nnet1 <- train(results~ ., data = tr, >> >>>>> method = "nnet", >> >>>>> >> >>>>> metric = "MAE", >> >>>>> trControl = ctrl, >> >>>>> >> >>>>> preProc = c("center", "scale", "zv"), >> >>>>> tuneGrid = data.frame(decay = (1), >> >>>>> size = (1.3801517))) >> >>>>> nnet1$results >> >>>>> >> >>>>> ///For SVM >> >>>>> >> >>>>> set.seed(30218) >> >>>>> svm1 <- train(results ~ ., data = tr, >> >>>>> method = "svmRadial", >> >>>>> >> >>>>> metric = "MAE", >> >>>>> preProc = c("center", "scale", "zv"), >> >>>>> trControl = ctrl, >> >>>>> tuneGrid=expand.grid(sigma = (0.5), >> >>>>> C = c(1.348657))) >> >>>>> getTrainPerf(svm1) >> >>>>> svm1$results >> >>>>> >> >>>>> //For GBM >> >>>>> >> >>>>> set.seed(30218) >> >>>>> gbm <- train(results ~ ., data = tr, >> >>>>> method = "gbm", >> >>>>> preProc = c("center", "scale", "zv"), >> >>>>> metric = "MAE", >> >>>>> >> >>>>> >> >>>>> tuneGrid = data.frame(n.trees = (200.09633523), >> >>>>> interaction.depth = (1), >> >>>>> shrinkage=(0.1), >> >>>>> n.minobsinnode=(10))) >> >>>>> gbm$results >> >>>>> >> >>>>> //Then the boxplot >> >>>>> >> >>>>> rvalues=resamples(list(nnet=nnet1, svm=svm1, GBM=gbm)) >> >>>>> >> >>>>> bwplot(rvalues, metric="MAE") >> >>>>> >> >>>>> [[alternative HTML version deleted]] >> >>>>> >> >>>>> ______________________________________________ >> >>>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> >>>>> https://stat.ethz.ch/mailman/listinfo/r-help >> >>>>> PLEASE do read the posting guide >> >>>>> http://www.R-project.org/posting-guide.html >> >>>>> and provide commented, minimal, self-contained, reproducible code. >> >>>>> >> >>>> >> > >> > [[alternative HTML version deleted]] >> > >> >______________________________________________ >> >R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> >https://stat.ethz.ch/mailman/listinfo/r-help >> >PLEASE do read the posting guide >> >http://www.R-project.org/posting-guide.html >> >and provide commented, minimal, self-contained, reproducible code. >> >> -- >> Sent from my phone. Please excuse my brevity. >> >[[alternative HTML version deleted]]
Hi your code is not reproducible. I get error with> setwd("C:/Users/PC/Documents")Error in setwd("C:/Users/PC/Documents") : cannot change working directory>so probably any other line of your code gives me error too. Use dput(d) or dput(head(d)) to provide your data Cheers Petr> -----Original Message----- > From: R-help <r-help-bounces at r-project.org> On Behalf Of javed khan > Sent: Friday, February 21, 2020 10:00 AM > To: Jeff Newmiller <jdnewmil at dcn.davis.ca.us> > Cc: R-help <r-help at r-project.org> > Subject: Re: [R] Different number of resamples error > > The whole code is as follows: > > library(caret) > library(farff) > library(gbm) > library(nnet) > > setwd("C:/Users/PC/Documents") > d=readARFF("myresults.arff") > > index <- createDataPartition(d$results, p = .70,list = FALSE) tr <-d[index, ] ts <-> d[-index, ] > index_2 <- createFolds(tr$results, returnTrain = TRUE, list = TRUE) ctrl<-> trainControl(method = "repeatedcv", index = index_2) > > set.seed(30218) > nnet1 <- train(results~ ., data = tr, > method = "nnet", > > metric = "MAE", > trControl = ctrl, > > preProc = c("center", "scale", "zv"), > tuneGrid = data.frame(decay = (1), > size = (1.3801517))) nnet1$results > > ///For SVM > > set.seed(30218) > svm1 <- train(results ~ ., data = tr, > method = "svmRadial", > > metric = "MAE", > preProc = c("center", "scale", "zv"), > trControl = ctrl, > tuneGrid=expand.grid(sigma = (0.5), > C = c(1.348657))) > getTrainPerf(svm1) > svm1$results > > //For GBM > > set.seed(30218) > gbm <- train(results ~ ., data = tr, > method = "gbm", > preProc = c("center", "scale", "zv"), > metric = "MAE", > > > tuneGrid = data.frame(n.trees = (200.09633523),interaction.depth > (1),> shrinkage=(0.1), n.minobsinnode=(10)))gbm$results> > //Then the boxplot > > rvalues=resamples(list(nnet=nnet1, svm=svm1, GBM=gbm)) > > bwplot(rvalues, metric="MAE") > > > On Fri, Feb 21, 2020 at 12:16 AM Jeff Newmiller <jdnewmil at dcn.davis.ca.us> > wrote: > > > You are being way too cavalier about what packages you are using. Read > > the Posting Guide about contributed packages... this list cannot > > provide expert support for every package out there. This confusion is > > why you should be providing a reproducible example when you ask for help > about R. > > > > The caret package depends on lattice and provides some overloaded > > versions of the bwplot function that do have a metric argument. I have > > no expertise with caret myself... but recommend that you supply a > > reproducible example for best luck in prompting someone to look closer. > > > > On February 20, 2020 1:31:30 PM PST, javed khan > > <javedbtk111 at gmail.com> > > wrote: > > >Thanks for your reply. > > > > > >I am not using any specific package for bwplot. I just used caret, > > >nnet and gbm packages. > > > > > >When I use resample (instead of resamples), it give me error message. > > > > > >metric=MAE gives the MAE values at x-axis when I used simple plots in > > >the recent past. > > > > > >Best regards > > > > > >On Thu, Feb 20, 2020 at 10:29 PM Bert Gunter <bgunter.4567 at gmail.com> > > >wrote: > > > > > >> cc the list! > > >> (which I have done here) > > >> > > >> Bert Gunter > > >> > > >> "The trouble with having an open mind is that people keep coming > > >along and > > >> sticking things into it." > > >> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > >> > > >> > > >> On Thu, Feb 20, 2020 at 1:20 PM javed khan <javedbtk111 at gmail.com> > > >wrote: > > >> > > >>> Thanks for your reply. > > >>> > > >>> I am not using any specific package for bwplot. I just used caret, > > >nnet > > >>> and gbm packages. > > >>> > > >>> When I use resample (instead of resamples), it give me error > > >message. > > >>> > > >>> metric=MAE gives the MAE values at x-axis when I used simple plots > > >in the > > >>> recent past. > > >>> > > >>> Best regards > > >>> > > >>> On Thu, Feb 20, 2020 at 10:15 PM Bert Gunter > > ><bgunter.4567 at gmail.com> > > >>> wrote: > > >>> > > >>>> ?? > > >>>> Isn't is resample() not resamples()? > > >>>> From what package? > > >>>> What package is bwplot from? lattice:::bwplot has no "metric" > > >argument. > > >>>> > > >>>> > > >>>> > > >>>> Bert Gunter > > >>>> > > >>>> "The trouble with having an open mind is that people keep coming > > >along > > >>>> and sticking things into it." > > >>>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip > > >>>> ) > > >>>> > > >>>> > > >>>> On Thu, Feb 20, 2020 at 12:55 PM javed khan > > >>>> <javedbtk111 at gmail.com> > > >>>> wrote: > > >>>> > > >>>>> Hello to all > > >>>>> > > >>>>> I have different train functions for NN, SVM and GBM and when I > > >combine > > >>>>> the > > >>>>> results using bwplot, it gives me the error " Different number > > >>>>> of resamples in each model". It gives me the results (MAE > > >>>>> values) but using the boxplot, it gives the error. The code is > > >>>>> as follows: > > >>>>> > > >>>>> set.seed(30218) > > >>>>> nnet1 <- train(results~ ., data = tr, > > >>>>> method = "nnet", > > >>>>> > > >>>>> metric = "MAE", > > >>>>> trControl = ctrl, > > >>>>> > > >>>>> preProc = c("center", "scale", "zv"), > > >>>>> tuneGrid = data.frame(decay = (1), > > >>>>> size = (1.3801517))) > > >>>>> nnet1$results > > >>>>> > > >>>>> ///For SVM > > >>>>> > > >>>>> set.seed(30218) > > >>>>> svm1 <- train(results ~ ., data = tr, > > >>>>> method = "svmRadial", > > >>>>> > > >>>>> metric = "MAE", > > >>>>> preProc = c("center", "scale", "zv"), > > >>>>> trControl = ctrl, > > >>>>> tuneGrid=expand.grid(sigma = (0.5), > > >>>>> C > > >>>>> c(1.348657))) > > >>>>> getTrainPerf(svm1) > > >>>>> svm1$results > > >>>>> > > >>>>> //For GBM > > >>>>> > > >>>>> set.seed(30218) > > >>>>> gbm <- train(results ~ ., data = tr, > > >>>>> method = "gbm", > > >>>>> preProc = c("center", "scale", "zv"), > > >>>>> metric = "MAE", > > >>>>> > > >>>>> > > >>>>> tuneGrid = data.frame(n.trees = (200.09633523), > > >>>>> interaction.depth = (1), > > >>>>> shrinkage=(0.1), > > >>>>> n.minobsinnode=(10))) > > >>>>> gbm$results > > >>>>> > > >>>>> //Then the boxplot > > >>>>> > > >>>>> rvalues=resamples(list(nnet=nnet1, svm=svm1, GBM=gbm)) > > >>>>> > > >>>>> bwplot(rvalues, metric="MAE") > > >>>>> > > >>>>> [[alternative HTML version deleted]] > > >>>>> > > >>>>> ______________________________________________ > > >>>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, > > >>>>> see https://stat.ethz.ch/mailman/listinfo/r-help > > >>>>> PLEASE do read the posting guide > > >>>>> http://www.R-project.org/posting-guide.html > > >>>>> and provide commented, minimal, self-contained, reproducible code. > > >>>>> > > >>>> > > > > > > [[alternative HTML version deleted]] > > > > > >______________________________________________ > > >R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > > >https://stat.ethz.ch/mailman/listinfo/r-help > > >PLEASE do read the posting guide > > >http://www.R-project.org/posting-guide.html > > >and provide commented, minimal, self-contained, reproducible code. > > > > -- > > Sent from my phone. Please excuse my brevity. > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guidehttp://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code.
structure(list(recordnumber = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 84, 89, 91, 92, 93, 94, 97, 98, 99, 100, 101), projectname = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 7L, 7L, 1L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 5L, 5L, 7L, 7L, 8L, 8L, 8L, 8L, 3L, 8L, 4L, 4L, 4L), .Label = c("de", "erb", "gal", "X", "hst", "slp", "spl", "Y"), class = "factor"), cat2 = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 3L, 3L, 13L, 9L, 9L, 9L, 11L, 11L, 11L, 5L, 4L, 6L, 8L, 3L, 3L, 9L, 9L, 9L, 9L, 9L, 6L, 7L, 2L, 2L, 3L, 3L, 8L, 8L, 8L, 13L, 13L, 13L, 8L, 8L, 14L, 6L, 4L, 3L, 10L, 10L, 10L, 14L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 10L, 8L, 8L, 1L, 1L, 1L, 1L, 1L, 12L, 1L, 1L, 1L, 1L, 1L, 1L, 12L), .Label c("Avionics", "application_ground", "avionicsmonitoring", "batchdataprocessing", "communications", "datacapture", "launchprocessing", "missionplanning", "monitor_control", "operatingsystem", "realdataprocessing", "science", "simulation", "utility"), class = "factor"), forg = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("f", "g"), class = "factor"), center = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 6L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 2L, 2L, 2L, 6L, 6L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 2L, 2L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 2L, 2L, 2L), .Label = c("1", "2", "3", "4", "5", "6"), class = "factor"), year = c(1979, 1979, 1979, 1979, 1979, 1979, 1979, 1982, 1980, 1980, 1984, 1980, 1985, 1980, 1983, 1982, 1980, 1984, 1983, 1984, 1985, 1985, 1985, 1986, 1986, 1986, 1982, 1982, 1982, 1982, 1982, 1982, 1985, 1987, 1987, 1986, 1986, 1986, 1986, 1986, 1980, 1975, 1982, 1982, 1982, 1977, 1977, 1984, 1980, 1983, 1984, 1985, 1979, 1979, 1979, 1979, 1977, 1979, 1974, 1975, 1976, 1979, 1971, 1980, 1979, 1977, 1976, 1983, 1978, 1979, 1979, 1979, 1979, 1982, 1978, 1978, 1978, 1979, 1984, 1984, 1980, 1980, 1977, 1977, 1977, 1977, 1977, 1977, 1982, 1980, 1983, 1983, 1983), mode = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("embedded", "organic", "semidetached" ), class = "factor"), rely = structure(c(4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 4L, 4L, 2L, 3L, 3L, 5L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 3L, 4L, 5L, 3L, 4L, 4L, 3L, 3L, 4L, 4L, 5L, 2L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), data = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 2L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 3L, 3L, 3L, 4L, 4L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 2L, 2L, 3L, 3L, 2L, 2L, 5L, 4L, 3L, 3L, 3L, 5L, 4L, 2L, 2L, 4L, 4L, 4L, 4L, 2L, 4L, 3L, 3L, 3L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), cplx = structure(c(4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 3L, 3L, 3L, 4L, 6L, 4L, 4L, 4L, 5L, 4L, 4L, 4L, 5L, 4L, 6L, 4L, 6L, 6L, 3L, 3L, 4L, 4L, 4L, 2L, 4L, 3L, 4L, 4L, 4L, 3L, 3L, 4L, 5L, 5L, 5L, 5L, 5L, 4L, 5L, 5L, 5L, 5L, 5L, 6L, 5L, 5L, 5L, 5L, 5L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), time = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 6L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 5L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 5L, 5L, 5L, 4L, 4L, 4L, 5L, 3L, 3L, 6L, 3L, 4L, 4L, 3L, 3L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 6L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 5L, 6L, 5L, 5L, 5L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), stor = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 6L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 6L, 3L, 3L, 6L, 3L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 3L, 3L, 5L, 3L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 5L, 5L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), virt = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 4L, 3L, 2L, 2L, 2L, 3L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 2L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 2L, 2L, 3L, 3L, 3L, 3L, 2L, 3L, 4L, 4L, 4L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), turn = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 2L, 3L, 4L, 2L, 2L, 3L, 3L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 4L, 4L, 3L, 3L, 3L, 3L, 2L, 3L, 2L, 3L, 4L, 4L, 4L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), acap = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 4L, 4L, 3L, 4L, 4L, 4L, 3L, 4L, 4L, 4L, 4L, 3L, 3L, 5L, 4L, 3L, 4L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 4L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), aexp = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 5L, 5L, 5L, 5L, 4L, 5L, 3L, 5L, 4L, 5L, 4L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 4L, 4L, 4L, 4L, 4L, 3L, 4L, 4L, 5L, 3L, 3L, 5L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 4L, 5L, 5L, 4L, 4L, 4L, 4L, 2L, 4L, 3L, 3L, 3L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), pcap = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 5L, 4L, 5L, 3L, 4L, 4L, 3L, 5L, 4L, 4L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 3L, 4L, 4L, 3L, 3L, 4L, 5L, 5L, 3L, 3L, 4L, 4L, 4L, 3L, 3L, 3L, 5L, 5L, 3L, 4L, 5L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 4L, 5L, 5L, 4L, 4L, 4L, 4L, 3L, 4L, 3L, 3L, 3L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), vexp = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 3L, 3L, 2L, 3L, 1L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 4L, 1L, 1L, 4L, 4L, 4L, 4L, 1L, 4L, 2L, 2L, 2L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), lexp = structure(c(4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 1L, 4L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 4L, 3L, 3L, 4L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 3L, 4L, 4L, 4L, 4L, 3L, 3L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 4L, 1L, 1L, 4L, 4L, 4L, 4L, 2L, 4L, 2L, 2L, 2L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), modp = structure(c(4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 3L, 3L, 4L, 3L, 3L, 4L, 4L, 4L, 4L, 3L, 2L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 1L, 3L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 4L, 3L, 3L, 3L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), tool = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 3L, 3L, 1L, 4L, 3L, 3L, 2L, 3L, 3L, 4L, 2L, 2L, 2L, 5L, 5L, 5L, 4L, 3L, 3L, 1L, 2L, 4L, 4L, 2L, 2L, 3L, 1L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 5L, 5L, 3L, 3L, 4L, 4L, 3L, 3L, 3L, 3L, 4L, 3L, 3L, 3L, 3L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), sced = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 4L, 3L, 4L, 3L, 4L, 4L, 4L, 4L, 3L, 3L, 2L, 2L, 2L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("vl", "l", "n", "h", "vh", "xh"), class = "factor"), equivphyskloc = c(25.9, 24.6, 7.7, 8.2, 9.7, 2.2, 3.5, 66.6, 7.5, 20, 6, 100, 11.3, 100, 20, 100, 150, 31.5, 15, 32.5, 19.7, 66.6, 29.5, 15, 38, 10, 15.4, 48.5, 16.3, 12.8, 32.6, 35.5, 5.5, 10.4, 14, 6.5, 13, 90, 8, 16, 177.9, 302, 282.1, 284.7, 79, 423, 190, 47.5, 21, 78, 11.4, 19.3, 101, 219, 50, 227, 70, 0.9, 980, 350, 70, 271, 90, 40, 137, 150, 339, 240, 144, 151, 34, 98, 85, 20, 111, 162, 352, 165, 60, 100, 32, 53, 41, 24, 165, 65, 70, 50, 7.25, 233, 16.3, 6.2, 3), act_effort = c(117.6, 117.6, 31.2, 36, 25.2, 8.4, 10.8, 352.8, 72, 72, 24, 360, 36, 215, 48, 360, 324, 60, 48, 60, 60, 300, 120, 90, 210, 48, 70, 239, 82, 62, 170, 192, 18, 50, 60, 42, 60, 444, 42, 114, 1248, 2400, 1368, 973, 400, 2400, 420, 252, 107, 571.4, 98.8, 155, 750, 2120, 370, 1181, 278, 8.4, 4560, 720, 458, 2460, 162, 150, 636, 882, 444, 192, 576, 432, 72, 300, 300, 240, 600, 756, 1200, 97, 409, 703, 1350, 480, 599, 430, 4178.2, 1772.5, 1645.9, 1924.5, 648, 8211, 480, 12, 38)), row.names = c(NA, -93L), class = "data.frame") On Fri, Feb 21, 2020 at 10:06 AM PIKAL Petr <petr.pikal at precheza.cz> wrote:> Hi > > your code is not reproducible. > > I get error with > > > setwd("C:/Users/PC/Documents") > Error in setwd("C:/Users/PC/Documents") : cannot change working directory > > > > so probably any other line of your code gives me error too. > > Use dput(d) or dput(head(d)) to provide your data > > Cheers > Petr > > > -----Original Message----- > > From: R-help <r-help-bounces at r-project.org> On Behalf Of javed khan > > Sent: Friday, February 21, 2020 10:00 AM > > To: Jeff Newmiller <jdnewmil at dcn.davis.ca.us> > > Cc: R-help <r-help at r-project.org> > > Subject: Re: [R] Different number of resamples error > > > > The whole code is as follows: > > > > library(caret) > > library(farff) > > library(gbm) > > library(nnet) > > > > setwd("C:/Users/PC/Documents") > > d=readARFF("myresults.arff") > > > > index <- createDataPartition(d$results, p = .70,list = FALSE) tr <- > d[index, ] ts <- > > d[-index, ] > > index_2 <- createFolds(tr$results, returnTrain = TRUE, list = TRUE) ctrl > <- > > trainControl(method = "repeatedcv", index = index_2) > > > > set.seed(30218) > > nnet1 <- train(results~ ., data = tr, > > method = "nnet", > > > > metric = "MAE", > > trControl = ctrl, > > > > preProc = c("center", "scale", "zv"), > > tuneGrid = data.frame(decay = (1), > > size = (1.3801517))) nnet1$results > > > > ///For SVM > > > > set.seed(30218) > > svm1 <- train(results ~ ., data = tr, > > method = "svmRadial", > > > > metric = "MAE", > > preProc = c("center", "scale", "zv"), > > trControl = ctrl, > > tuneGrid=expand.grid(sigma = (0.5), > > C = c(1.348657))) > > getTrainPerf(svm1) > > svm1$results > > > > //For GBM > > > > set.seed(30218) > > gbm <- train(results ~ ., data = tr, > > method = "gbm", > > preProc = c("center", "scale", "zv"), > > metric = "MAE", > > > > > > tuneGrid = data.frame(n.trees = (200.09633523), > interaction.depth > > (1), > > shrinkage=(0.1), n.minobsinnode=(10))) > gbm$results > > > > //Then the boxplot > > > > rvalues=resamples(list(nnet=nnet1, svm=svm1, GBM=gbm)) > > > > bwplot(rvalues, metric="MAE") > > > > > > On Fri, Feb 21, 2020 at 12:16 AM Jeff Newmiller < > jdnewmil at dcn.davis.ca.us> > > wrote: > > > > > You are being way too cavalier about what packages you are using. Read > > > the Posting Guide about contributed packages... this list cannot > > > provide expert support for every package out there. This confusion is > > > why you should be providing a reproducible example when you ask for > help > > about R. > > > > > > The caret package depends on lattice and provides some overloaded > > > versions of the bwplot function that do have a metric argument. I have > > > no expertise with caret myself... but recommend that you supply a > > > reproducible example for best luck in prompting someone to look closer. > > > > > > On February 20, 2020 1:31:30 PM PST, javed khan > > > <javedbtk111 at gmail.com> > > > wrote: > > > >Thanks for your reply. > > > > > > > >I am not using any specific package for bwplot. I just used caret, > > > >nnet and gbm packages. > > > > > > > >When I use resample (instead of resamples), it give me error message. > > > > > > > >metric=MAE gives the MAE values at x-axis when I used simple plots in > > > >the recent past. > > > > > > > >Best regards > > > > > > > >On Thu, Feb 20, 2020 at 10:29 PM Bert Gunter <bgunter.4567 at gmail.com> > > > >wrote: > > > > > > > >> cc the list! > > > >> (which I have done here) > > > >> > > > >> Bert Gunter > > > >> > > > >> "The trouble with having an open mind is that people keep coming > > > >along and > > > >> sticking things into it." > > > >> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > > > >> > > > >> > > > >> On Thu, Feb 20, 2020 at 1:20 PM javed khan <javedbtk111 at gmail.com> > > > >wrote: > > > >> > > > >>> Thanks for your reply. > > > >>> > > > >>> I am not using any specific package for bwplot. I just used caret, > > > >nnet > > > >>> and gbm packages. > > > >>> > > > >>> When I use resample (instead of resamples), it give me error > > > >message. > > > >>> > > > >>> metric=MAE gives the MAE values at x-axis when I used simple plots > > > >in the > > > >>> recent past. > > > >>> > > > >>> Best regards > > > >>> > > > >>> On Thu, Feb 20, 2020 at 10:15 PM Bert Gunter > > > ><bgunter.4567 at gmail.com> > > > >>> wrote: > > > >>> > > > >>>> ?? > > > >>>> Isn't is resample() not resamples()? > > > >>>> From what package? > > > >>>> What package is bwplot from? lattice:::bwplot has no "metric" > > > >argument. > > > >>>> > > > >>>> > > > >>>> > > > >>>> Bert Gunter > > > >>>> > > > >>>> "The trouble with having an open mind is that people keep coming > > > >along > > > >>>> and sticking things into it." > > > >>>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip > > > >>>> ) > > > >>>> > > > >>>> > > > >>>> On Thu, Feb 20, 2020 at 12:55 PM javed khan > > > >>>> <javedbtk111 at gmail.com> > > > >>>> wrote: > > > >>>> > > > >>>>> Hello to all > > > >>>>> > > > >>>>> I have different train functions for NN, SVM and GBM and when I > > > >combine > > > >>>>> the > > > >>>>> results using bwplot, it gives me the error " Different number > > > >>>>> of resamples in each model". It gives me the results (MAE > > > >>>>> values) but using the boxplot, it gives the error. The code is > > > >>>>> as follows: > > > >>>>> > > > >>>>> set.seed(30218) > > > >>>>> nnet1 <- train(results~ ., data = tr, > > > >>>>> method = "nnet", > > > >>>>> > > > >>>>> metric = "MAE", > > > >>>>> trControl = ctrl, > > > >>>>> > > > >>>>> preProc = c("center", "scale", "zv"), > > > >>>>> tuneGrid = data.frame(decay = (1), > > > >>>>> size = (1.3801517))) > > > >>>>> nnet1$results > > > >>>>> > > > >>>>> ///For SVM > > > >>>>> > > > >>>>> set.seed(30218) > > > >>>>> svm1 <- train(results ~ ., data = tr, > > > >>>>> method = "svmRadial", > > > >>>>> > > > >>>>> metric = "MAE", > > > >>>>> preProc = c("center", "scale", "zv"), > > > >>>>> trControl = ctrl, > > > >>>>> tuneGrid=expand.grid(sigma = (0.5), > > > >>>>> C > > > >>>>> c(1.348657))) > > > >>>>> getTrainPerf(svm1) > > > >>>>> svm1$results > > > >>>>> > > > >>>>> //For GBM > > > >>>>> > > > >>>>> set.seed(30218) > > > >>>>> gbm <- train(results ~ ., data = tr, > > > >>>>> method = "gbm", > > > >>>>> preProc = c("center", "scale", "zv"), > > > >>>>> metric = "MAE", > > > >>>>> > > > >>>>> > > > >>>>> tuneGrid = data.frame(n.trees = (200.09633523), > > > >>>>> interaction.depth = (1), > > > >>>>> shrinkage=(0.1), > > > >>>>> n.minobsinnode=(10))) > > > >>>>> gbm$results > > > >>>>> > > > >>>>> //Then the boxplot > > > >>>>> > > > >>>>> rvalues=resamples(list(nnet=nnet1, svm=svm1, GBM=gbm)) > > > >>>>> > > > >>>>> bwplot(rvalues, metric="MAE") > > > >>>>> > > > >>>>> [[alternative HTML version deleted]] > > > >>>>> > > > >>>>> ______________________________________________ > > > >>>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, > > > >>>>> see https://stat.ethz.ch/mailman/listinfo/r-help > > > >>>>> PLEASE do read the posting guide > > > >>>>> http://www.R-project.org/posting-guide.html > > > >>>>> and provide commented, minimal, self-contained, reproducible > code. > > > >>>>> > > > >>>> > > > > > > > > [[alternative HTML version deleted]] > > > > > > > >______________________________________________ > > > >R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > > > >https://stat.ethz.ch/mailman/listinfo/r-help > > > >PLEASE do read the posting guide > > > >http://www.R-project.org/posting-guide.html > > > >and provide commented, minimal, self-contained, reproducible code. > > > > > > -- > > > Sent from my phone. Please excuse my brevity. > > > > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]