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ISRO CS 2023 Q.65: solution and answer

ISRO 2023 · CSQ.65 · 1 mark · MCQ

Which of the following clustering technique is used by K- Means Algorithm:

  1. (A)

    Hierarchical Technique

  2. (B)

    Partitional technique

  3. (C)

    Divisive

  4. (D)

    Agglomerative

See the question in the paper
ISRO CS 2023 question 65Tap to open full size

Answer and solution

ANSWER

The answer is (b): K-Means is a partitional clustering technique.

Official answer: BSource: ISRO's revised and final answer key of 16 February 2024

  1. K-Means takes a fixed number of clusters and splits the data into non-overlapping groups in a single flat partition.

  2. It starts with centroids, assigns each point to its nearest centroid, recomputes each centroid as the mean of its points, and repeats until the assignments stop changing.

  3. A method that builds one flat set of disjoint clusters directly from the data is called a partitional (partitioning) technique. So K-Means is partitional.

  4. Hierarchical clustering builds a nested tree of clusters (a dendrogram) and needs no preset . K-Means builds no such tree, so (a) is wrong.

  5. Divisive clustering is a top-down hierarchical method that starts with all points in one cluster and splits it. It is hierarchical, so (c) is wrong.

  6. Agglomerative clustering is a bottom-up hierarchical method that starts with each point alone and merges the closest clusters. It is hierarchical, so (d) is wrong.

KEY IDEA

Clustering methods are either partitional (one flat set of disjoint clusters, as in K-Means) or hierarchical (a nested tree, built top-down by divisive or bottom-up by agglomerative methods).

WATCH OUT FOR

Choosing hierarchical, divisive or agglomerative because they are also well-known clustering names. K-Means needs a preset and builds no dendrogram, so it is not hierarchical.

From the ISRO CS 2023 paper. Every question of this paper · The full paper (PDF, ISRO) · All 1 ISRO Clustering question, with notes