library(randomForest)
library(rpart)
library(caret)
library(plyr)
library(e1071)
# Build test data
data(iris)
Y.reg <- iris[, 1]
X.reg <- model.matrix(~ ., iris[, -1])
X.class <- X.reg
Y.class <- factor(ifelse(iris$Sepal.Length <= 6.2, "No", "Yes"))
# Reusable control
myControl_reg <- trainControl(
method = "cv", number = 10,
p = 0.75, savePrediction = TRUE,
classProbs = FALSE, returnResamp = "final",
returnData = TRUE)
myControl_class <- trainControl(
method = "cv", number = 10,
p = 0.75, savePrediction = TRUE,
summaryFunction=twoClassSummary,
classProbs = TRUE, returnResamp = "final",
returnData = TRUE)
# Regression
set.seed(482)
suppressWarnings({
models.reg <- caretList(
x = X.reg,
y = Y.reg,
methodList=c("rf", "glm", "rpart", "treebag"),
trControl=myControl_reg
)
})
# Classification
set.seed(482)
suppressWarnings({
models.class <- caretList(
x = X.class,
y = Y.class,
metric="ROC",
methodList=c("rf", "glm", "rpart", "treebag"),
trControl=myControl_class
)
})
# Save
usethis::use_data(
models.reg, models.class,
Y.reg, Y.class,
X.reg, X.class,
overwrite=TRUE
)
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