# Split the data into training and testing sets
set.seed(2023)
index <- sample(1:nrow(iris), nrow(iris) * 0.8)
train_data <- iris[index,]
test_data <- iris[-index,]
ctrl1 <- caret::trainControl(method = "none")
# Train a dummy classifier with caret
dummy_model <- caret::train(Species ~ ., data = train_data,
method = dummyClassifier,
strategy = "stratified",
trControl = ctrl1)
# Make predictions using the trained dummy classifier
pred_vec <- predict(dummy_model, test_data)
# Evaluate the performance of the dummy classifier
conf_matrix <- caret::confusionMatrix(pred_vec, test_data$Species)
print(conf_matrix)
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