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Machine Learning Practice End Term: 10 May 2026 (January 2026 term)

Question 1

+4 marksOne correct option

Which variant of the Naive Bayes Classifier will be most suitable to predict the Gender in the given dataset?

Which variant of the Naive Bayes Classifier will be most suitable to predict the Gender in the given dataset?
  1. A

    CategoricalNB

  2. B

    BernoulliNB

  3. C

    MultinomialNB

  4. D

    GaussianNB

Question 2

+4 marksOne correct option

Consider the following time series analysis code:

In the above code, what is the primary role of the parameter d=1 in order=(1,1,1)?

Consider the following time series analysis code:
  1. A

    It controls the number of lag observations in the model

  2. B

    It represents the number of times the data is differenced

  3. C

    It defines the size of the moving average window

  4. D

    It determines the forecast horizon

Question 3

+4 marksOne correct option

In the following question, an Assertion (A) is followed by a Reason (R). Choose the correct option from the choices given below: Assertion (A): In classification problems, precision should always be maximized over recall Reason (R): Recall is independent of false negatives

  1. A

    Both A and R are true, and R is the correct explanation of A

  2. B

    Both A and R are true, but R is not the correct explanation of A

  3. C

    A is true, but R is false

  4. D

    A is false, but R is true

  5. E

    Both A and R are false

23 more questions in this paper

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More on the MLP End Term 10 May 2026 paper

The IIT Madras BS Machine Learning Practice (MLP) End Term paper sat on 10 May 2026, in the January 2026 term: 26 questions for 101 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.

FeatureMLP End Term 10 May 2026 at a glance
TermJanuary 2026 term
SubjectMachine Learning Practice
Course codeBSCS2008
Questions26
Marks101
Duration180 min
MCQ9
Written8
MSQ9
Official paperMachine Learning Practice 06 May 26
Negative markingNo negative marking.
Updated

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