COMP 337/COMP 527: The Understanding of the Perceptron Algorithm - IT Assignment Help

Assignment Task:

 Learning outcome assessed

(1) A critical awareness of current problems and research issues in data mining.

(2) The ability to consistently apply knowledge concerning current data mining research issues in an original manner and produce work which is at the forefront of current developments in the sub-discipline of data mining.

Purpose of assessment

This assignment assesses the understanding of the Perceptron algorithm by implementing a binary Perceptron for text clustering. Marking criteria Marks for each question are indicated under the corresponding question.

1. Objectives 

This assignment requires you to implement the Perceptron algorithm using the Python programming language. 

Questions/Tasks 

(1) Explain the Perceptron algorithm for the binary classification case, providing its pseudo code. 

(2) Prove that for a linearly separable dataset, perceptron algorithm will converge.

(3) Implement a binary perceptron.

(4) Use the binary perceptron to train classifiers to discriminate between

(a) class 1 and class 2,

(b) class 2 and class 3 and

(c) class 1 and class 3.

Report the train and test classification accuracies for each of the three classifiers after 20 iterations. Which pair of classes is most difficult to separate?

(5) For the classifier (a) implemented in part (4) above, which feature is the most discriminative?

(6) Extend the binary perceptron that you implemented in part (2) above to perform multi-class classification using the 1-vs-rest approach. Report the train and test classification accuracies for each of the three classes after training for 20 iterations.

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