gamSpline Caret 包

Question

How to choose the optimal df(degrees of freedom) for my splines. I use poisson regression and splines that helps me to adjust for non linear changes. Using the caret package, train function with method = gamSpline the function test only 3 df.

model <- train(
  RBC ~ elapsed, 
  obgyn_aleph,
  method = "gamSpline",
  trControl = trainControl(
    method = "cv", 
    number = 10,
    verboseIter = TRUE
  )
)

Aggregating results Selecting tuning parameters Fitting df = 3 on full training set

Is it the default? if so how I can change it?

Tnx, Daniel

Answer 1

The tuneGrid argument allows the user to specify a custom grid of tuning parameters, in this case, df

 model <- train(
      RBC ~ elapsed, 
      obgyn_aleph,
      method = "gamSpline",
      trControl = trainControl(
        method = "cv", 
        number = 10,
        verboseIter = TRUE
      ),
      tuneGrid = data.frame(df=seq(2,20,by=2))
    )