Match the items in Column 1 with the items in Column 2 in the following table:…
2024
Match the items in Column 1 with the items in Column 2 in the following table:
Column 1Column 2(p) Principal Component Analysis
(q) Naïve Bayes Classification (r)
Logistic Regression
(i) Discriminative Model
(ii) Dimensionality Reduction
(iii) Generative Model
- A.
(p) − (iii), (q) − (i), (r) − (ii)
- B.
(p) − (ii), (q) − (i), (r) − (iii)
- C.
(p) − (ii), (q) − (iii), (r) − (i)
- D.
(p) − (iii), (q) − (ii), (r) − (i)
Attempted by 17 students.
Show answer & explanation
Correct answer: C
Correct matching: (p) Principal Component Analysis → (ii) Dimensionality Reduction; (q) Naïve Bayes Classification → (iii) Generative Model; (r) Logistic Regression → (i) Discriminative Model.
Principal Component Analysis is an unsupervised technique that transforms features to a lower-dimensional space while preserving variance, so it is used for dimensionality reduction.
Naïve Bayes models the joint distribution by estimating class priors and class-conditional likelihoods (P(X|Y) and P(Y)); because it models how data is generated per class, it is a generative model.
Logistic Regression directly models the conditional probability P(Y|X) and focuses on decision boundaries between classes, so it is a discriminative model.