Consider a Naive Bayes problem with three features, f_1, f_2 and f_3 for a binary classification problem. We have a total of 6 training samples given in the table below: | Sample | f_1 | f_2 | f_3 | y | |---|---|---|---|---| | x_1 | 0 | 1 | 1 | 0 | | x_2 | 1 | 0 | 1 | 0 | | x_3 | 0 | 0 | 1 | 0 | | x_4 | 0 | 0 | 0 | 1 | | x_5 | 1 | 0 | 1 | 1 | | x_6 | 0 | 1 | 0 | 1 | For x_{test} = \begin{bmatrix} 1 & 1 & 0 \end{bmatrix}^T, what output would Naive Bayes model predict assuming that no Laplacian smoothing has been done as part of the algorithm?

Machine Learning Techniques · Quiz 2 · 16 Mar 2025 · January 2025 term

Question 9: Consider a Naive Bayes problem with three features, f_1, …

Question 9

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Consider a Naive Bayes problem with three features, $f_1, f_2$ and $f_3$ for a binary classification problem. We have a total of 6 training samples given in the table below:

Sample	$f_1$	$f_2$	$f_3$	$y$
$x_1$	0	1	1	0
$x_2$	1	0	1	0
$x_3$	0	0	1	0
$x_4$	0	0	0	1
$x_5$	1	0	1	1
$x_6$	0	1	0	1

For $x_{test} = \begin{bmatrix} 1 & 1 & 0 \end{bmatrix}^T$ , what output would Naive Bayes model predict assuming that no Laplacian smoothing has been done as part of the algorithm?

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Question 9 of 14 in the IIT Madras BS Machine Learning Techniques (MLT) Quiz 2 paper sat on 16 Mar 2025, in the January 2025 term (IIT M DIPLOMA AN EXAM QDD2 16 Mar 2025). It carries 4 marks.

Question 9: Consider a Naive Bayes problem with three features, f_1, …

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