# alternative way to do the same
if (!requireNamespace("dbscan", quietly = TRUE)) {
    install.packages("dbscan")
}
library(dbscan)

# Create example data: 50 points in 2D space
set.seed(123)
data <- matrix(rnorm(100), ncol=2)  # 50 observations, 2 features

# Perform DBSCAN
dbscan_result <- dbscan(data, eps = 0.5, minPts = 5)

# Print clustering results
print(dbscan_result)

# Basic scatter plot with clustering results
plot(data, col = ifelse(dbscan_result$cluster == 0, "grey", as.factor(dbscan_result$cluster)), pch = 20, main="DBSCAN Clustering", xlab="Feature 1", ylab="Feature 2")
legend("topright", legend=c("Noise", unique(dbscan_result$cluster)), col=c("grey", unique(as.factor(dbscan_result$cluster))), pch=20)