GATE DA 2024 | Question 18

MCQ · 1 mark · −0.33

Match the items in Column 1 with the items in Column 2 in the following table:

Column 1Column 2
(p) Principal Component Analysis(i) Discriminative Model
(q) Naïve Bayes Classification(ii) Dimensionality Reduction
(r) Logistic Regression(iii) Generative Model
  1. Option A: (p) − (iii), (q) − (i), (r) − (ii)
  2. Option B: (p) − (ii), (q) − (i), (r) − (iii)
  3. Option C: (p) − (ii), (q) − (iii), (r) − (i) (correct)
  4. Option D: (p) − (iii), (q) − (ii), (r) − (i)

Answer

(C)

Explanation

Match each method by what it learns.

  • (p) Principal Component Analysis projects the data onto the few directions of largest variance, keeping most of the information in fewer features: dimensionality reduction, (ii).
  • (q) Naïve Bayes models how the data are generated, through \(P(\text{class})\) and \(P(\text{features} \mid \text{class})\), and gets the class from Bayes' theorem: a generative model, (iii).
  • (r) Logistic regression models \(P(\text{class} \mid \text{features})\) directly and never models the features themselves: a discriminative model, (i).

Options A and D call PCA a generative model, and B swaps the two classifiers.

Answer: C