data(iris)
set.seed(42)
kmeans_result <- kmeans(iris[, 1:4], centers = 3)
plot(iris$Sepal.Length, iris$Sepal.Width,
col = kmeans_result$cluster,
pch = 19,
main = "K-Means Clustering (Base R)")# 4. Add Cluster Centers (the "centroids")
points(kmeans_result$centers[, 1], kmeans_result$centers[, 2],
col = 1:3, pch = 8, cex = 2) [cite: 506]
table(iris$Species, kmeans_result$cluster)
