Help understanding an error Line Search Fails
Just found your tutorial, wow! I am going to see if I can figure out how or if my data is applicable to this process. https://bbolker.github.io/mixedmodels-misc/ecostats_chap.html Thanks again WHP From: Ben Bolker <bbolker at gmail.com> Sent: Thursday, December 6, 2018 11:20 AM To: Bill Poling <Bill.Poling at zelis.com>; r-sig-mixed-models at r-project.org Subject: Re: [R-sig-ME] Help understanding an error Line Search Fails You could ask your question on r-help or StackOverflow or CrossValidated (https://stats.stackexchange.com). r-help is mostly for R questions (obviously). StackOverflow might be best, as this is primarily a programming question (and you're already looking on SO for answers ...) There's a whole lot of information & advice on constructing reproducible examples here: https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example If you choose to post on SO or CV, make sure to read the info on "how to post"; for R-help, read https://www.r-project.org/posting-guide.html good luck, Ben Bolker
On 2018-12-06 7:36 a.m., Bill Poling wrote:
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 <mailto:r-sig-mixed-models-bounces at r-project.org> On Behalf Of Ben Bolker Sent: Wednesday, December 5, 2018 12:48 PM To: mailto:r-sig-mixed-models at 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 Confidentiality Notice This message is sent from Zelis. ...{{dropped:13}}
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