Clustering-KMeans-nd-KMedoids

Suppose a cluster contain the points {(1, 3), (3, 3), (2, 1)}. What is the centroid of the cluster?

• (2, 2.33)

• (2.33, 2)

• (2, 3)

• None

Suppose the initial cluster centres are (1, 1) and (2, 1) . These points belongs to clusters C1 and C2 respectively. Apply KMeans clustering to find the cluster to be assigned for the point (4, 3) after the first pass?

• C1

• C2

• None

Which Clustering algorithm is suitable if the data type is categorical?

• K-Means

• K-Medoids

• K-Median

• K-Mode

Which of the following statements about KMeans algorithm are true?

• K-Means algorithm can determine spherical shaped clusters

• Number of clusters to be determined must be specified

• Sensitive to noise and outliers

• KMeans is a density based algorithm

Which of the following statements about KMedoids algorithm are true?

• K-Medoids algorithm can determine spherical shaped clusters

• Number of clusters to be determined must be specified

• Less sensitive to noise data than KMeans

• Suitable for large volume of data (Scalable)