# Install and load the ggplot2 package

install.packages("ggplot2")

library(ggplot2)

# Load the iris dataset

data(iris)

# Display the first 6 rows of the iris dataset

head(iris)

# Create a scatter plot using ggplot2 to visualize Petal.Length vs. Petal.Width with color indicating Species

ggplot(iris, aes(Petal.Length, Petal.Width, color = Species)) + geom_point()

# Perform k-means clustering on the Petal.Length and Petal.Width columns with 3 clusters

irisCluster <- kmeans(iris[, 3:4], 3, nstart = 20)

# Print information about the clustering results

print(irisCluster)

# Create a confusion matrix to compare the clustering results with actual species labels

conf_matrix <- table(irisCluster$cluster, iris$Species)

# Calculate accuracy based on the confusion matrix

accuracy = sum((diag(conf_matrix)))/sum(conf_matrix)

# Print the accuracy

print(accuracy)