Predict method for mlS3 caret wrapper

# S3 method for class 'wrap_caret'
predict(object, newx, type = NULL, ...)

Arguments

object: Object from wrap_caret
newx: New features (matrix or data frame)
type: Prediction type: "raw" (default), "class", "prob", or NULL
...: Additional arguments to caret::predict.train

Value

Vector or matrix of predictions

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