The GATE Grind

GATE 2026 DA – Question 23

Machine Learning · Supervised learning: classification · 1 mark · Multiple select

In the following table, the Task column lists a few tasks related to machine learning. The Algorithm column lists a few algorithms.

Each entry 't' from the Task column is to be matched with an appropriate entry 'a' from the Algorithm column such that the task 't' can be solved using the algorithm 'a'. Denote such a match as t:a

TaskAlgorithm
T1 – ClusteringA1 – Markov Chain Monte Carlo
T2 – ClassificationA2 – K-Medoid
T3 – SamplingA3 – Linear Discriminant Analysis
T4 – Feature ExtractionA4 – Naive Bayes

Which of the following options is/are the correct matching(s)?

  1. T1:A4, T2:A3, T3:A1, T4:A2
  2. T1:A2, T2:A4, T3:A1, T4:A3
  3. T1:A3, T2:A4, T3:A1, T4:A2
  4. T1:A4, T2:A2, T3:A1, T4:A3

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Show answer and explanation

Correct answer: (B) T1:A2, T2:A4, T3:A1, T4:A3

Explanation

K-medoid groups points into clusters, so it matches clustering (T1:A2). Naive Bayes is a classifier (T2:A4). Markov chain Monte Carlo is a way of drawing samples (T3:A1). Linear discriminant analysis finds the directions that best separate the classes, so it extracts features (T4:A3). Only option B has all four matches right.