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DC203 Pages: 2

3 and Y value 5. Find the classification of this new paper from the data of trained
samples using KNN algorithm.
OR (6)

b) Write a note on Bayes theorem and illustrate the method for predicting
(6) probabilities with an example.

a) Differentiate Simple Linear Regression & Multiple linear regression with an

(6) example.
OR
b) Explain the divide and conquer approach for the construction of decision
(6) trees with an example.
a) Explain any 3 characteristics of neural networks? (6)
OR
b) How does a Perceptron learn the appropriate weights using delta rule? (6)
a) How SVM handles non- linearly separable data. (6)
OR
b) How Classification using hyper planes is possible? What is Maximum Margin

(6)
Hyperplane?

a) How will you evaluate the performance of a model using confusion matrices? Justify

answer using the statistics - Accuracy, Precision and (6) Recall.

OR
b) How ensembles learning improve model performance? Explain any two
(6) ensemble based methods.
Fok

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