We Discuss About That NPTEL Introduction to Machine Learning Assignment 7 Answer
NPTEL Introduction to Machine Learning Assignment 7 Answer – Here All The Questions and Answers Provided to Help All The Students and NPTEL Candidate as a Reference Purpose, It is Mandetory to Submit Your Weekly Assignment By Your Own Understand Level.
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NPTEL Introduction to Machine Learning Assignment
With the increased availability of data from varied sources there has been increasing attention paid to the various data driven disciplines such as analytics and machine learning. In this course we intend to introduce some of the basic concepts of machine learning from a mathematically well motivated perspective. We will cover the different learning paradigms and some of the more popular algorithms and architectures used in each of these paradigms.
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This course can have Associate in Nursing unproctored programming communication conjointly excluding the Proctored communication, please check announcement section for date and time. The programming communication can have a weightage of twenty fifth towards the ultimate score.
- Assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
- ( All assignments in a particular week will be counted towards final scoring – quizzes and programming assignments).Â
- Unproctored programming exam score = 25% of the average scores obtained as part of Unproctored programming exam – out of 100
- Proctored Exam score =50% of the proctored certification exam score out of 100
UNPROCTORED PROGRAMMING EXAM SCORE >=10/25 AND PROCTORED EXAM SCORE >= 20/50.Â
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1. You have 2 binary classifiers A and B. A has accuracy=0% and B has accuracy=50%. Which classifier is more useful?
a. A
b. B
c. Both are good
d. Cannot say
Answer:- C
2. You have 2 multi-class classifiers A and B. A has accuracy=0% and B has accuracy=50%. Which classifier is more useful?
a. A
b. B
c. Both are good
d. Cannot say
Answer:- D
NPTEL Introduction to Machine Learning Assignment 7 Answers
3. Using the bootstrap approach for sampling, the new dataset will have _________ of the original samples on expectation.
a. 50.0%
b. 56.8%
c. 63.2%
d. 73.6%
Answer:- A
4. You have a special case where your data has 10 classes and is sorted according to target labels. You attempt 5-fold cross validation by selecting the folds sequentially. What can you say about your resulting model?
a. It will have 100% accuracy.
b. It will have 0% accuracy.
c. Accuracy will depend on how good the model does.
d. Accuracy will depend on the compute power available for training.
Answer:- D
5. Given the following information
What is the precision and recall?
a. 0.5, 0.4375
b. 0.7, 0.636
c. 0.6, 0.636
d. 0.7, 0.4375
e. None of the above
Answer:- E
6. AUC for your newly trained model is 0.5. Is your model prediction completely random?
a. Yes
b. No
c. ROC curve is needed to derive this conclusion
d. Cannot be determined even with ROC
Answer:- D
NPTEL Introduction to Machine Learning Assignment 7 Answers
7. What is the effect of using bagging on weak classifiers for variance?
a. Increases variance
b. Reduces variance
c. Does not change
Answer:- A
8. You are building a model to detect cancer. Which metric will you prefer for evaluating your model?
a. Accuracy
b. Sensitivity
c. Specificity
d. MSE
Answer:- C
9. You are building a model to detect a mild medical condition for which further testing costs are extremely expensive. Which metric will you prefer for evaluating your model?
a. Accuracy
b. Sensitivity
c. Specificity
d. MSE
Answer:- D
10. A: Boosting takes many weak learners and combines them into a strong learner.
B: Boosting determines the proportion of importance each weak learner should be assigned and weighs its prediction by it and combines them to make the final prediction.
a. A is True. B is True. B is the correct explanation for A.
b. A is True. B is True. B is not the correct explanation for A.
c. A is True. B is False.
d. Both A and B are False.
Answer:- C
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