K-Means Clustering Quiz

What is the first step in the K-Means algorithm?

• Select K

• Randomly select initial cluster seeds

• Calculate distance from each object to each cluster seed

• Assign each object to the closest cluster

What does K-means clustering depend on?

• Choosing the value of k

• The number of clusters

• The distance metric

• The initial placement of centroids

What is one advantage of K-means clustering?

• It is simple to implement

• It is sensitive to outliers

• It can handle small datasets

• It requires labeled data

What is a disadvantage of K-means clustering?

• It can discover patterns in unlabeled data

• It is fast

• The initial placement of centroids can affect the final clustering

• It produces clusters that are easy to interpret

Fill in the blank: Clustering is the use of unsupervised techniques for grouping ______.