[R] Different number of resamples error

[javed khan]

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 using 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 using 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 using 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 using 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]]
>>>>
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>>>>
>>>

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