Download DBATU B.Tech 2019 Oct-Nov CSE 1st Sem Machine Learning Question Paper

DR. BABASAHEB AMBEDKAR TECHNOLOGICAL UNIVERSITY, LONERE

Mid Semester Examination – September 2019

Course: T.Y. B.Tech (CSE)
Subject Name: Machine Learning
Max Marks: 20

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Instructions to the Students:

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1. Check that you have received a correct Question paper.
2. Assume suitable data if necessary and mention it clearly.
3. Draw NEAT labeled diagrams wherever necessary.

Q.1. Attempt any Six Questions (1*6 = 6 Marks)

1. Define Hypothesis Space.

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2. What is information gain?
3. What is the difference between supervised and unsupervised learning?
4. What is cross validation?
5. Write Bayes' theorem.
6. Define confusion matrix with a suitable example.

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7. What is SVM?

Q. 2. Attempt any Two of the following (2*3 = 6 Marks)

1. Explain the problem of overfitting in ML?
2. Differentiate Linear Vs Logistic regression. Give a suitable example of each.
3. Apply KNN for the following dataset and predict the class of the test example (A1 = 3, A2 = 7). Assume K=3.

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Q.3. Attempt any One of the following (1*8 = 8 Marks)

1. Explain Bayesian Learning and Naïve Bayes Classifier. Solve the following example:
   A patient takes a lab test and the result comes back positive. The test returns a correct positive result in only 98% of the cases in which the disease is actually present, and a correct negative result in only 97% of the cases in which the disease is not present. Furthermore, .008 of the entire population has this cancer. Find P(cancer|+) and P(-cancer|+).
2. Illustrate the operation of ID3 for the following training example. Consider Information Gain as Attribute Selection Measure.
   PlayTennis: training examples
   

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   Day	Outlook	Temperature	Humidity	Wind	Play Tennis
   D1	Sunny	Hot	High	Weak	No
   D2	Sunny	Hot	High	Strong	No
   D3	Overcast	Hot	High	Weak	Yes
   D4	Rain	Mild	High	Weak	Yes
   D5	Rain	Cool	Normal	Weak	Yes
   D6	Rain	Cool	Normal	Strong	No
   D7	Overcast	Cool	Normal	Strong	Yes
   D8	Sunny	Mild	High	Weak	No
   D9	Sunny	Cool	Normal	Weak	Yes
   D10	Rain	Mild	Normal	Weak	Yes
   D11	Sunny	Mild	Normal	Strong	Yes
   D12	Overcast	Mild	High	Strong	Yes
   D13	Overcast	Hot	Normal	Weak	Yes
   D14	Rain	Mild	High	Strong	No

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