[R-sig-ME] Help understanding an error Line Search Fails

[Bill Poling]

Good morning Ben and thank you for your response.

Yes, had not considered this a sig-mixed-models question but was unsure of where to start my questions.

How would I make available a reproducible example for further help?

If you suggest that this may be more suitable data for mixed model I would like to pursue that.

Appreciate your help Sir, thank you.

WHP




From: R-sig-mixed-models <r-sig-mixed-models-bounces using r-project.org> On Behalf Of Ben Bolker
Sent: Wednesday, December 5, 2018 12:48 PM
To: r-sig-mixed-models using r-project.org
Subject: Re: [R-sig-ME] Help understanding an error Line Search Fails


As far as I can tell none of the model types you're using fall under
the category of "mixed models" (linear/generalized linear models with
data identified in known groups that are to be estimated by some form
of shrinkage estimator/"random effect"). (Please feel free to correct me!)

By the way, I don't think it makes any sense to use "ProviderID" as a
*numeric* predictor variable ... that (and ProductID) are places where
you *might* actually want to use a mixed model.

This looks like more of a CrossValidated question - note that you'll
have to provide a *reproducible* example in order to get help ...

cheers
Ben Bolker

On 2018-12-05 12:45 p.m., Bill Poling wrote:
>
>
> Good afternoon. I hope I have provided enough info to get my question answered.
>
>> I am running windows 10 -- R3.5.1 -- RStudio Version 1.1.456
>
>
> Using caret package I have been comparing models using my data, a training subset N=17357.
>
> I have run PLS, RDA, GLM, and Boosted Logit based on a couple of tutorials.
>
> http://dataaspirant.com/2017/01/19/support-vector-machine-classifier-implementation-r-caret-package/
>
> https://cran.r-project.org/web/packages/caret/vignettes/caret.html
>
> https://topepo.github.io/caret/model-training-and-tuning.html
>
> However, when I get to trying svmLinear or svmRadial they both produce error: line search fails -1.614732 -0.257144 0.00001920624 0.00001369617 -0.00000001857456 -0.00000001542947 -0.000000000000568072
>
> I have done some googling research but cannot find a definitive answer as to why this model does not work with my data but the other models do?
>
> https://stackoverflow.com/questions/43267209/line-search-fails-when-training-a-model-using-caret
>
> https://stackoverflow.com/questions/15895897/line-search-fails-in-training-ksvm-prob-model
>
>
>
> Any advice would be appreciated.
>
> Thank you
>
> WHP
>
> str(training)
>
> # 'data.frame':17357 obs. of 7 variables:
> # $ SavingsReversed: num 0 0 0 0 0 ...
> # $ productID : num 3 3 3 3 3 1 3 3 3 1 ...
> # $ ProviderID : num 113676 114278 114278 114278 114278 ...
> # $ ModCnt : num 0 1 1 1 1 1 1 0 0 1 ...
> # $ B2 : num -1 -1 -1 -1 -1 -1 7 9 9 -1 ...
> # $ B1a : num 1 1 1 1 1 1 26 26 26 3 ...
> # $ EditnumberI : Factor w/ 2 levels "Bad","Good": 1 2 2 2 2 2 1 1 2 2 ...
>
>
> head(training, n=25)
>
> # SavingsReversed productID ProviderID ModCnt B2 B1a EditnumberI
> # 1 0.00 3 113676 0 -1 1 Bad
> # 5 0.00 3 114278 1 -1 1 Good
> # 6 0.00 3 114278 1 -1 1 Good
> # 7 0.00 3 114278 1 -1 1 Good
> # 8 0.00 3 114278 1 -1 1 Good
> # 10 0.00 1 114278 1 -1 1 Good
> # 12 128.25 3 116641 1 7 26 Bad
> # 13 159.60 3 116641 0 9 26 Bad
> # 14 0.00 3 116641 0 9 26 Good
> # 15 0.00 1 117280 1 -1 3 Good
> # 16 1622.55 3 117439 1 9 26 Good
> # 17 60.07 3 117439 1 9 26 Good
> # 18 0.00 3 117439 0 -1 3 Good
> # 19 190.00 3 117962 0 9 26 Good
> # 20 372.66 3 119316 0 1 26 Bad
> # 22 0.00 3 120431 1 -1 1 Good
> # 25 0.00 3 121319 1 7 26 Bad
> # 26 18.79 3 121319 1 7 26 Bad
> # 27 23.00 3 121319 1 7 26 Bad
> # 28 18.79 3 121319 1 7 26 Bad
> # 29 0.00 3 121319 1 7 26 Bad
> # 30 25.86 3 121319 2 7 26 Bad
> # 31 14.00 3 121319 1 7 26 Bad
> # 36 113.00 3 121545 1 1 26 Bad
> # 37 197.20 3 121545 1 9 26 Bad
>
>
> anyNA(training)
> #[1] FALSE
>
> My scripts
>
> ctrl <- trainControl(
> method = "repeatedcv",
> repeats = 3,
> classProbs = TRUE,
> summaryFunction = twoClassSummary
> )
>
> set.seed(123)
> svm_Linear <- train(EditnumberI ~., data = training,
> method = "svmLinear",
> trControl = ctrl,
> preProcess = c("center", "scale"),
> tuneLength = 10,
> metric="ROC")
> #warnings()
> svm_Linear
>
>
>
> set.seed(123)
> svm_Radial <- train(EditnumberI ~., data = training,
> method = "svmRadial",
> trControl = ctrl,
> preProcess = c("center", "scale"),
> tuneLength = 10,
> metric="ROC")
> #warnings()
> svm_Radial
>
>
>
> line search fails -1.614732 -0.257144 0.00001920624 0.00001369617 -0.00000001857456 -0.00000001542947 -0.000000000000568072
>
>
>
> WHP
>
>
>
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