Question

Which of the following is incorrect about k-Means Clustering?

(a) k-means clustering produces a dendrogram

(b) It classifies data through a single step partition

(c) It is a divisive approach

(d) In this method, data are partitioned into k-clusters, which are prespecified at the outset

The question was asked during an online interview.

I want to ask this question from Microarray-Based Approaches in division Functional Genomics & Proteomics of Bioinformatics

Answer 1

Right choice is (a) k-means clustering produces a dendrogram

Easiest explanation: In contrast to hierarchical clustering algorithms, k-means clustering does not produce a dendrogram, but instead classifies data through a single step partition. The value of k is normally randomly set but can be adjusted if results are found to be unsatisfactory.