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library(caret)
install.packages("mlbench")
library(mlbench)
data(Sonar)
# Corrected code
head(Sonar)
# Make a custom trainControl
myControl <- trainControl(
method = "cv",
number = 10,
summaryFunction = twoClassSummary,
classProbs = TRUE, # <- Super important!
verboseIter = TRUE
)
install.packages("glmnet")
library(glmnet)

model <- train(
  Class ~ ., 
  data = Sonar,
  tuneGrid = expand.grid(
    alpha = 0:1,
    lambda = seq(0.0001, 1, length = 20)
  ),
  method = "glmnet",
  trControl = myControl
)

model

max(model[["results"]][["ROC"]])

plot(model)
predict(model, Sonar)