How to make svm_linear work with tune_grid/tune_race_anova

Question

So when I try to tune cost for svm_linear with tidymodels approach, it fails every time, but it works just fine with svm_rbf function, so I cannot understand where the problem comes from

rcpsvm<-recipe(Species~.,data=iris)
svmlin<-svm_linear(cost=tune())%>%
   set_engine("LiblineaR")%>%
  set_mode("classification")
svmlinwrkfl<-workflow()%>%
  add_recipe(rcpsvm)%>%
  add_model(svmlin)
gridwals<-expand_grid(cost=c(0.01, 0.1, 1, 10, 100))
folds<-vfold_cv(iris, strata=Species, 5)
tunelin<-tune_grid(svmlinwrkfl, grid = gridwals, folds)

And then it says that all models failed cause No data available in table What I'm doing wrong?

Answer 1

The specific model you are using cannot generate class probabilities, only hard class predictions, so you need to tune using a metric for classes (not a metric for probabilities). An example of this is sensitivity:

library(tidymodels)
#> Registered S3 method overwritten by 'tune':
#>   method                   from   
#>   required_pkgs.model_spec parsnip
data(two_class_dat)

data_train <- two_class_dat[-(1:10), ]
data_test  <- two_class_dat[  1:10 , ]
folds <- bootstraps(data_train, times = 5)


svm_cls_spec <- 
  svm_linear(cost = tune()) %>% 
  set_mode("classification") %>% 
  set_engine("LiblineaR")


workflow(Class ~ ., svm_cls_spec) %>%
  tune_grid(folds, grid = 5, metrics = metric_set(sensitivity))
#> # Tuning results
#> # Bootstrap sampling 
#> # A tibble: 5 × 4
#>   splits            id         .metrics         .notes          
#>   <list>            <chr>      <list>           <list>          
#> 1 <split [781/296]> Bootstrap1 <tibble [5 × 5]> <tibble [0 × 1]>
#> 2 <split [781/286]> Bootstrap2 <tibble [5 × 5]> <tibble [0 × 1]>
#> 3 <split [781/296]> Bootstrap3 <tibble [5 × 5]> <tibble [0 × 1]>
#> 4 <split [781/291]> Bootstrap4 <tibble [5 × 5]> <tibble [0 × 1]>
#> 5 <split [781/304]> Bootstrap5 <tibble [5 × 5]> <tibble [0 × 1]>

^{Created on 2022-01-28 by the reprex package (v2.0.1)}