Text Clustering

K-means is an iterative algorithm, some steps need to be done repeatedly. Which are the repeated steps?

• Assign each point to its nearest cluster

• Update the cluster centroids based on the current assignment

• Using the elbow method to choose K

• Test on the test dataset

What is the minimum number of variables/features required to perform clustering? 

• 0

• 1

• 2

• 3

If we run K-Means clustering twice, is it expected to get the same clustering results?

• Yes

• No

• Yes, as long as we use the same data

• Yes, as long as we use the same distance measure

The ideal clustering results should have _

• High intra-cluster similarity

• Low intra-cluster similarity

• High inter-cluster similarity

• Low inter-cluster similarity