This function reduces a data set to 2 dimensions using principle component analysis (PCA) and colours clusters of points.

This function reduces a data set to 2 dimensions using principle component analysis (PCA) and colours clusters of points.

show_clusters(X, clusters, centroids)

Arguments

X	array Data points of dimension (n,d)
clusters	array Cluster assignments for each point in X, dimension (n,1)
centroids	array Coordinates of cluster centers, dimension (k,d)

Value

plot A 2d principal components scatter plot coloured by cluster

Examples

X = rbind(c(0,0), c(1,0), c(10,0), c(11,0))
centers = rbind(c(0, 0), c(10, 10))
labels <- c(1,1,1,1)
show_clusters(X, labels,centers)