[R] Different number of resamples error
Bert Gunter
bgunter@4567 @end|ng |rom gm@||@com
Thu Feb 20 22:29:21 CET 2020
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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