Machine Learning — Summer 2021

Write a short note on- (1) machine learning (2) training data and test data (3) perceptron (4) for Bayes theorem P(h|D) =_______ (5) PAC framework (6) linear regression (7) case based reasoning

Write down the steps for designing the learning system by appropriate example.

Explain FIND-Salgorithm with example. Compare with candidate elimination algorithm.

Give decision trees to represent the following Boolean functions:

P V [Q ^ R]

[P ^ Q] v [R ^S]

What is decision tree? Explain various issues in the Decision Tree learning.

Define ANN. Write the derivation of weight update rule for BPNN.

Explain Bayesian Belief Network with example.

Differentiate the following:

Gradient Descent and Stochastic Gradient Descent (ii) Neural network and artificial neural network

Explain Naïve Bayes classification algorithm for text classification.

Compare FOIL and FOCL algorithm.

What is sequential learning algorithm? Explain with help of Learn-One-Rule paradigm

Explain First Order Combined Learner (FOCL) algorithm with example.

How prior knowledge is used in Explanation based learning? Explain with help of PROLOG-EBG algorithm.

What is reinforcement learning? What is the purpose of reward in this kind of learning?

Write down working of K Nearest Neighbor Algorithm with example.

Compare supervised, unsupervised and reinforcement algorithm with suitable example.

Discuss the application areas of machine learning algorithms.