Highlights
Objectives
This assignment requires you to implement the Perceptron algorithm using the Python programming language.
Assignment description
Inside, you will find two files: train.data and test.data, corresponding respectively to the train and test data to be used in this assignment. Each line in the file represents a different train/test instance. The first four values (separated by commas) are feature values for four features. The last element is the class label (class-1, class-2 or class-3).
Questions/Tasks
1. Explain the Perceptron algorithm for the binary classification case, providing its pseudo code.
2. Implement a binary perceptron.
3. Use the binary perceptron to train classifiers to discriminate between
• class 1 and class 2,
• class 2 and class 3, and
• class 1 and class 3.
Report the train and test classification accuracies for each of the three classifiers after training for 20 iterations. Which pair of classes is most difficult to separate?
4. Extend the binary perceptron that you implemented in part 3 above to perform multi-class classification using the 1-vs-rest approach. Report the train and test classification accuracies after training for 20 iterations.
5. Add an `2 regularisation term to your multi-class classifier implemented in part 4. Set the regularisation coefficient to 0.01, 0.1, 1.0, 10.0, 100.0 and compare the train and test classification accuracies.
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