Wrap caret models for mlS3

Minimal wrapper around caret::train with no tuning. Hyperparameters can be passed via ... as named arguments.

wrap_caret(x, y, method = "rf", ...)

Arguments

x

Feature matrix or data frame

y

Response vector

method

caret model method (default "rf")

...

Named hyperparameters (e.g., mtry = 3, ntree = 500)

Value

Object with class "mlS3_caret"

Examples

# Only runs if caret is installed

data(mtcars)

# Prepare data
X_reg <- mtcars[, -1]  # All except mpg
y_reg <- mtcars$mpg     # Target variable

# Split into train/test
set.seed(123)
idx_reg <- sample(nrow(X_reg), 0.7 * nrow(X_reg))
X_train <- X_reg[idx_reg, ]
y_train <- y_reg[idx_reg]
X_test <- X_reg[-idx_reg, ]
y_test <- y_reg[-idx_reg]

mod <- wrap_caret(X_train, y_train, method = "rf", mtry = 3)
(pred <- predict(mod, X_test))
#>           Mazda RX4       Mazda RX4 Wag      Hornet 4 Drive             Valiant 
#>            20.03772            19.98929            19.71554            19.46125 
#>          Merc 450SE          Merc 450SL Lincoln Continental       Toyota Corona 
#>            15.36817            15.33221            12.97337            24.25431 
#>          Camaro Z28    Pontiac Firebird 
#>            15.32682            15.97900