DWDM2

data = iris
head(data)

sampler = sample(1:nrow(data), size = 0.9*nrow(data), replace = FALSE)
training_data = data[sampler,]
testing_data = data[-sampler,]

test_data_label = testing_data[,5]
training_data_label = training_data[,5]

test_data = testing_data[-5]
training_data = training_data[,-5]

model = naiveBayes(training_data, training_data_label)
prediction = predict(model, test_data)

library(caret)

table(prediction, test_data_label)
confusionMatrix(prediction, test_data_label)