K-means Clustering- Viva Quiz

K-means clustering is an example of

• Bottom up Clustering
• Hierarchical clustering
• Partitioning Clustering

Example of Bottom up clustering

• Agglomatory Clustering
• Divisive Clustering
• Both

What should be the best choice of no. of clusters based on the following

• Minimum K value in Elbow curve
• Maximum K value in Elbow curve
• Average K value in Elbow curve

_________ is the most powerful language for Data Science.

• R
• C
• Python

_______ gives information about top level data.

• Head
• Tail
• Frame

What is the primary objective of K-means clustering?

• To minimize the distance between points in the same cluster

• To maximize the distance between different clusters

• To create a hierarchical structure of clusters

Which of the following is a limitation of K-means clustering?

• It requires the number of clusters to be specified in advance

• It can handle non-spherical clusters well

• It is not sensitive to outliers

In K-means clustering, what does the term 'centroid' refer to?

• The farthest point from any cluster

• The average distance between all points in a dataset

• The point that represents the center of a cluster

What is a common initialization method used in K-means clustering?

• Choosing the first K points in the dataset

• Using the mean of the dataset

• Randomly selecting K points from the dataset

What is the purpose of the elbow method in K-means clustering?

• To visualize the clusters

• To determine the optimal number of clusters

• To assess the quality of the clusters