Are you looking for NPTEL Introduction to Machine Learning Assignment Week 7 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 Bootstrapping & Cross Validation, Class Evaluation Measures, ROC curve, MDL, Ensemble Methods – Bagging, Committee Machines and Stacking, and Boosting. The correct answers are marked in Green Color with a tick sign.

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NPTEL Introduction to Machine Learning Assignment Week 7 Answers

1. For the given confusion matrix, compute the recall

For the given confusion matrix, compute the recall
  1. 0.73
  2. 0.7
  3. 0.6
  4. 0.67
  5. 0.78
  6. None of the above

2. Pallavi is working on developing a binary classifier that has a huge class imbalance. Which of the following metric should she optimize the classifier over to develop a good model?

  1. Accuracy
  2. Precision
  3. Recall
  4. F-Score

3. While designing an experiment, which of these aspects should be considered?

  1. Floor/Ceiling Effects
  2. Order Effects
  3. Sampling Bias

4. Which of the following are true
TP- True Positive, TN – True Negative, FP – False Positive, FN – False Negative

  1. Precision = TP/TP + FP
  2. Recall = TP/TP + FN
  3. Accuracy = 2(TP +TN)/TP + TN+ FP + FN
  4. Recall = FP/TP + FP

5. In the ROC plot, what are the quantities along y and x axes respectively?

  1. Precision, Recall
  2. Recall, Precision,
  3. True Positive Rate, False Positive Rate
  4. False Positive Rate, True Positive Rate
  5. Specificity, Sensitivity
  6. True Positive, True Negative
  7. True Negative, True Positive

6. How does bagging help in improving the classification performance?

  1. If the parameters of the resultant classifiers are fully uncorrelated (independent), then bagging is inefficient.
  2. It helps reduce variance
  3. If the parameters of the resultant classifiers are fully correlated, then bagging is inefficient
  4. It helps reduce bias

7. Which method among bagging and stacking should be chosen in case of limited training data? and What is the appropriate reason for your preference

  1. Bagging, because we can combine as many classifier as we want by training each on a different sample of the training data
  2. Bagging, because we use the same classification algorithms on all samples of the training data
  3. Stacking, because we can use different classification algorithms on the training data
  4. Stacking, because each classifier is trained on all of the available data

8. Which of the following statements are TRUE when comparing Committee Machines and Stacking

  1. Committee Machines are, in general, special cases of 2-layer stacking where the second- layer classifier provides uniform weightage.
  2. Both Committee Machines and Stacking have similar mechanisms, but Stacking uses different classifiers while Committee Machines use similar classifiers.
  3. Committee Machines are more powerful than Stacking
  4. Committee Machines are less powerful than Stacking
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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