tuning naive Bayes classifier with Caret in R

Question

I train a model with following code, however, I can't find out how can I change the tunegrid because the FL and Adjust were held constantly at specific value.(my dataset is categorical)

Activity_nb <- train(Actx, Acty,data = Dact, method = "nb", trControl =   myc1,metric = "Accuracy",importance = TRUE)
Naive Bayes 

2694 samples
4 predictor
4 classes: 'CC', 'CE', 'CW', 'HA' 

No pre-processing
Resampling: Cross-Validated (10 fold) 
Summary of sample sizes: 2425, 2424, 2426, 2425, 2425, 2423, ... 
Resampling results across tuning parameters:

usekernel  Accuracy   Kappa    
FALSE      0.8165804  0.6702313
TRUE      0.8165804  0.6702313

Tuning parameter 'fL' was held constant at a value of 0
Tuning parameter 'adjust' was held constant at a value of 1
Accuracy was used to select the optimal model using  the largest value.
The final values used for the model were fL = 0, usekernel = FALSE and    adjust = 1.

Answer 1

grid <- data.frame(fL=c(0,0.5,1.0), usekernel = TRUE, adjust=c(0,0.5,1.0))

Activity_nb <- train(..., tuneGrid=grid, ...)

hope this helps.