Figure from the original question paper

(A) PCA has reduced the dimensionality of the dataset because the combinations of features are de-correlated.

(B) PCA has not reduced the dimensionality of the dataset because all principal components are retained.

(C) PCA always reduces the dimensionality of the dataset regardless of the number of components retained.

(D) PCA can never be used for dimensionality reduction.

Figure from the original question paper

(A) Option figure from the original question paper

(B) Option figure from the original question paper

(C) Option figure from the original question paper

(D) Option figure from the original question paper

MLT End Term: 31 August 2025, Set QDD1 (May 2025 term)

Question 1

+3 marksOne correct option

A
PCA has reduced the dimensionality of the dataset because the combinations of features are de-correlated.
B
PCA has not reduced the dimensionality of the dataset because all principal components are retained.
C
PCA always reduces the dimensionality of the dataset regardless of the number of components retained.
D
PCA can never be used for dimensionality reduction.

Question 2

+3 marksOne correct option

Question 3

+4 marksOne correct option

Consider clustering 1D data with a mixture of 2 Gaussians using the EM algorithm. You are given the data points $x_1 = 1, x_2 = 10, x_3 = 20$ .

Suppose the output of the E-step is as follows:

$\begin{gathered} \lambda_1^1 = 1, \; \lambda_2^1 = 0 \\ \lambda_1^2 = 0.4, \; \lambda_2^2 = 0.6 \\ \lambda_1^3 = 0.1, \; \lambda_2^3 = 0.9, \end{gathered}$

where $\lambda_C^i$ denotes the probability of the $i$ -th data point to be in cluster $C$ . After performing the M-step for the means $\mu_1$ and $\mu_2$ , what are the updated means?

14 more questions in this paper

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More on the MLT End Term 31 Aug 2025 Set QDD1 paper

The IIT Madras BS Machine Learning Techniques (MLT) End Term paper sat on 31 Aug 2025, in the May 2025 term, set QDD1: 17 questions for 50 marks in 180 minutes. The first 3 questions are below. Sign in with Google — it is free — to see the whole paper with its answers and explanations, in learning mode or as a timed mock test.

Feature	MLT End Term 31 Aug 2025 Set QDD1 at a glance
Term	May 2025 term
Subject	Machine Learning Techniques
Course code	BSCS2007
Questions	17
Marks	50
Duration	180 min
MCQ	7
MSQ	4
Numerical	6
Official paper	IIT M DIPLOMA FN EXAM QDD1 31 Aug 2025
Negative marking	No negative marking.
Updated	25 Sept 2026

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Set QDB3