Artificial neural network (ANN) analysis in R using iris data

ANN.r

# Load data
data <- iris

# Split data into training and testing sets
set.seed(123)
index <- sample(1:nrow(data), 0.8 * nrow(data))
train <- data[index,]
test <- data[-index,]

# Build ANN model
library(caret)
model <- train(Species ~ ., data = train, method = "mlp", trControl = trainControl(method = "cv", number = 5))

# Make predictions on the test set
predictions <- predict(model, newdata = test)

# Evaluate the model's performance
confusionMatrix(predictions, test$Species)