Are you looking for NPTEL Introduction to Machine Learning Assignment Week 8 Answers? If yes, you will find the answers to the questions asked in the NPTEL Introduction to Machine Learning quiz exam here. If you are preparing for this exam this article will help you in finding the latest and updated answers.

There is a total of 8 questions related to Gradient Boosting, Random Forests, Multi-class Classification, Naive Bayes, Bayesian Networks. The correct answers are marked in Green Color with a tick sign.

Note: If the questions in the exam is not same/changed please share them with us, so that we update with the latest questions & answers

NPTEL Introduction to Machine Learning Assignment Week 8 Answers

1. Consider the two statements:

Statement 1: Gradient Boosted Decision Trees can overfit easily.
Statement 2: It is easy to parallelize Gradient Boosted Decision Trees.
Which of these are true?

  1. Both the statements are True.
  2. Statement 1 is true, and statement 2 is false.
  3. Statement 1 is false, and statement 2 is true.
  4. Both the statements are false.

2. A company hires you to look at their classification system for whether a given customer would potentially buy their product. When you check the existing classifier on different folds of the training set, you find that it manages a low

accuracy of usually around 60%.
Sometimes, it’s barely above 50%.

With this information in mind, and without using additional classifiers, which of the following ensemble methods
would you use to increase the classification accuracy effectively?

  1. Committee Machine
  2. AdaBoost
  3. Bagging
  4. Stacking

3. Which of the following algorithms don’t use learning rate as a hyperparameter?

  1. Random Forests
  2. Adaboost
  3. KNN
  4. OPCA

4. Consider the following data for 500 instances of home, 600 instances of office, and 700 instances of factory type buildings.

consider-the-following-data-for-500-instances-of-home-600-instances-of-office-and-700-instances-of-factory-type-buildings

Suppose a building has a balcony and power-backup but is not multi-storied. According to the Naive Bayes algorithm, it is of type

  1. Home
  2. Office
  3. Factory

5. A dataset with two classes is plotted below.

A dataset with two classes is plotted below.

Does the data satisfy the Naive Bayes assumption?

  1. Yes
  2. No
  3. The given data is insufficient
  4. None of these

6. Which of these statements is/are True about Random Forests?

  1. The goal of random forests is to increase the correlation between the trees
  2. The goal of random forests is to decrease the correlation between the trees.
  3. In Random Forests, each decision tree fits the residuals from the previous one; thus, the correlation between the trees won’t matter
  4. None of these

7. Consider the below dataset:

Consider the below dataset:

Suppose you have to classify a test example “The ball won the race to the boundary” and are asked to compute P(Cricket | “The ball won the race to the boundary”), what is an issue that you will face if you are using Naive Bayes Classifier, and how will you work around it? Assume you are using word frequencies to estimate all the probabilities.

  1. There won’t be a problem, and the probability of P(Cricket |”The ball won the race to the boundary”) will be equal to 1.
  2. Problem: A few words that appear at test time do not appear in the dataset.
    Solution: Smoothing.
  3. Problem: A few words that appear at test time appear more than once in the dataset
    Solution: Remove those words from the dataset.
  4. None of these

8. Consider the two statements:

Statement 1: Bayesian Networks need not always be Directed Acyclic Graphs (DAGs)
Statement 2: Each node in a bayesian network represents a random variable, and each edge represents conditional dependence.
Which of these are true?

  1. Both the statements are True.
  2. Statement 1 is true, and statement 2 is false.
  3. Statement 1 is false, and statement 2 is true.
  4. Both the statements are false.
NPTEL Introduction to Machine Learning Assignment Answers

FAQ

What is NPTEL Introduction to Machine Learning?

NPTEL Introduction to Machine Learning Course is an online free course by IIT Madras that has been developed by Prof. Balaraman Ravindran. The main aim of this course is to provide the basic concepts of machine learning from a mathematically well-motivated perspective.

Are These Answers Correct?

Yes, all these answers are 100% correct.

Are These Answers Updated?

Yes, these answers are up to date with the latest questions.

Will I Get a Certificate?

Yes, you will get a certificate but it costs ₹1000 exam fee.

Wrap Up

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