Figure from the passage in the original paper Based on the above data, answer the given subquestions. Figure from the original question paper Derive the maximum likelihood estimate of the parameter\ in terms of the training examples 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

Consider the following dataset with 4 features {f_1, f_2, f_3, f_4} and three labels y = 0, -1, +1. Assume the features to be binary. Answer the given subquestions under the Naive Bayes assumptions. | Sample | f_1 | f_2 | f_3 | f_4 | y | |---|---|---|---|---|---| | 1 | 1 | 0 | 1 | 0 | 0 | | 2 | 0 | 1 | 0 | 1 | 0 | | 3 | 1 | 1 | 0 | 0 | +1 | | 4 | 1 | 1 | 1 | 0 | +1 | | 5 | 0 | 0 | 1 | 1 | -1 | | 6 | 0 | 0 | 0 | 1 | -1 | Figure from the original question paper Figure from the original question paper Figure from the original question paper Figure from the original question paper Figure from the original question paper Find the maximum likelihood estimate\ and\ of\ ,\ , and , respectively.

(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 Quiz 2: 23 November 2025 (September 2025 term)

Question 1

+3 marksOne or more correct options

Based on the above data, answer the given subquestions.

Which of the following equations correctly represents the maximum likelihood problem for

estimating
?

Select all that apply.

Question 2

+4 marksOne correct option

Based on the above data, answer the given subquestions.

Derive the maximum likelihood estimate of the parameter
in terms of the training examples

Question 3

+2 marksOne correct option

Consider the following dataset with 4 features $\{f_1, f_2, f_3, f_4\}$ and three labels $y = 0, -1, +1$ . Assume the features to be binary. Answer the given subquestions under the Naive Bayes assumptions.

Sample	$f_1$	$f_2$	$f_3$	$f_4$	$y$
1	1	0	1	0	0
2	0	1	0	1	0
3	1	1	0	0	$+1$
4	1	1	1	0	$+1$
5	0	0	1	1	$-1$
6	0	0	0	1	$-1$

Find the maximum likelihood estimate
and
of
,
, and , respectively.

11 more questions in this paper

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More on the MLT Quiz 2 23 Nov 2025 paper

The IIT Madras BS Machine Learning Techniques (MLT) Quiz 2 paper sat on 23 Nov 2025, in the September 2025 term: 14 questions for 40 marks in 120 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 Quiz 2 23 Nov 2025 at a glance
Term	September 2025 term
Subject	Machine Learning Techniques
Course code	BSCS2007
Questions	14
Marks	40
Duration	120 min
MSQ	3
MCQ	7
Numerical	4
Official paper	IIT M DIPLOMA AN EXAM QDD2 23 Nov 2025 NEW
Negative marking	No negative marking.
Updated	25 Sept 2026