Objectives This requires you to implement the Perceptron algorithm using the Python programming language. NOTE No credit will be given for implementing any other types of classification algorithms or using an existing library for classification instead of implementing it by yourself. However, you are allowed to use numpy library for accessing data structures such as numpy.array. But it is not a requirement to use numpy. You must provide a README file describing how to run your code to re-produce your results.

Description Download the data.zip file. Inside, you will find two files: train.data and test.data, corresponding respectively to the train and test data to be used in this. 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.

Instructions 1. the source code for all your programs (do not provide ipython/jupyter/colab notebooks, instead submit standalone code in a single .py file),

2. a README file (plain text) describing how to compile/run your code to produce the various results required, and

3. a PDF file providing the answers to the questions. It is extremely important that you provide all the files described above and not just the source code! THE CODE SHOULD BE IN PYTHON

(THIS IS THE TEST DATA)

5.0,3.5,1.3,0.3,class-1 4.5,2.3,1.3,0.3,class-1 4.4,3.2,1.3,0.2,class-1 5.0,3.5,1.6,0.6,class-1 5.1,3.8,1.9,0.4,class-1 4.8,3.0,1.4,0.3,class-1 5.1,3.8,1.6,0.2,class-1 4.6,3.2,1.4,0.2,class-1 5.3,3.7,1.5,0.2,class-1 5.0,3.3,1.4,0.2,class-1 5.5,2.6,4.4,1.2,class-2 6.1,3.0,4.6,1.4,class-2 5.8,2.6,4.0,1.2,class-2 5.0,2.3,3.3,1.0,class-2 5.6,2.7,4.2,1.3,class-2 5.7,3.0,4.2,1.2,class-2 5.7,2.9,4.2,1.3,class-2 6.2,2.9,4.3,1.3,class-2 5.1,2.5,3.0,1.1,class-2 5.7,2.8,4.1,1.3,class-2 6.7,3.1,5.6,2.4,class-3 6.9,3.1,5.1,2.3,class-3 5.8,2.7,5.1,1.9,class-3 6.8,3.2,5.9,2.3,class-3 6.7,3.3,5.7,2.5,class-3 6.7,3.0,5.2,2.3,class-3 6.3,2.5,5.0,1.9,class-3 6.5,3.0,5.2,2.0,class-3 6.2,3.4,5.4,2.3,class-3 5.9,3.0,5.1,1.8,class-3

(THIS IS THE TRAIN DATA)

5.1,3.5,1.4,0.2,class-1 4.9,3.0,1.4,0.2,class-1 4.7,3.2,1.3,0.2,class-1 4.6,3.1,1.5,0.2,class-1 5.0,3.6,1.4,0.2,class-1 5.4,3.9,1.7,0.4,class-1 4.6,3.4,1.4,0.3,class-1 5.0,3.4,1.5,0.2,class-1 4.4,2.9,1.4,0.2,class-1 4.9,3.1,1.5,0.1,class-1 5.4,3.7,1.5,0.2,class-1 4.8,3.4,1.6,0.2,class-1 4.8,3.0,1.4,0.1,class-1 4.3,3.0,1.1,0.1,class-1 5.8,4.0,1.2,0.2,class-1 5.7,4.4,1.5,0.4,class-1 5.4,3.9,1.3,0.4,class-1 5.1,3.5,1.4,0.3,class-1 5.7,3.8,1.7,0.3,class-1 5.1,3.8,1.5,0.3,class-1 5.4,3.4,1.7,0.2,class-1 5.1,3.7,1.5,0.4,class-1 4.6,3.6,1.0,0.2,class-1 5.1,3.3,1.7,0.5,class-1 4.8,3.4,1.9,0.2,class-1 5.0,3.0,1.6,0.2,class-1 5.0,3.4,1.6,0.4,class-1 5.2,3.5,1.5,0.2,class-1 5.2,3.4,1.4,0.2,class-1 4.7,3.2,1.6,0.2,class-1 4.8,3.1,1.6,0.2,class-1 5.4,3.4,1.5,0.4,class-1 5.2,4.1,1.5,0.1,class-1 5.5,4.2,1.4,0.2,class-1 4.9,3.1,1.5,0.1,class-1 5.0,3.2,1.2,0.2,class-1 5.5,3.5,1.3,0.2,class-1 4.9,3.1,1.5,0.1,class-1 4.4,3.0,1.3,0.2,class-1 5.1,3.4,1.5,0.2,class-1 7.0,3.2,4.7,1.4,class-2 6.4,3.2,4.5,1.5,class-2 6.9,3.1,4.9,1.5,class-2 5.5,2.3,4.0,1.3,class-2 6.5,2.8,4.6,1.5,class-2 5.7,2.8,4.5,1.3,class-2 6.3,3.3,4.7,1.6,class-2 4.9,2.4,3.3,1.0,class-2 6.6,2.9,4.6,1.3,class-2 5.2,2.7,3.9,1.4,class-2 5.0,2.0,3.5,1.0,class-2 5.9,3.0,4.2,1.5,class-2 6.0,2.2,4.0,1.0,class-2 6.1,2.9,4.7,1.4,class-2 5.6,2.9,3.6,1.3,class-2 6.7,3.1,4.4,1.4,class-2 5.6,3.0,4.5,1.5,class-2 5.8,2.7,4.1,1.0,class-2 6.2,2.2,4.5,1.5,class-2 5.6,2.5,3.9,1.1,class-2 5.9,3.2,4.8,1.8,class-2 6.1,2.8,4.0,1.3,class-2 6.3,2.5,4.9,1.5,class-2 6.1,2.8,4.7,1.2,class-2 6.4,2.9,4.3,1.3,class-2 6.6,3.0,4.4,1.4,class-2 6.8,2.8,4.8,1.4,class-2 6.7,3.0,5.0,1.7,class-2 6.0,2.9,4.5,1.5,class-2 5.7,2.6,3.5,1.0,class-2 5.5,2.4,3.8,1.1,class-2 5.5,2.4,3.7,1.0,class-2 5.8,2.7,3.9,1.2,class-2 6.0,2.7,5.1,1.6,class-2 5.4,3.0,4.5,1.5,class-2 6.0,3.4,4.5,1.6,class-2 6.7,3.1,4.7,1.5,class-2 6.3,2.3,4.4,1.3,class-2 5.6,3.0,4.1,1.3,class-2 5.5,2.5,4.0,1.3,class-2 6.3,3.3,6.0,2.5,class-3 5.8,2.7,5.1,1.9,class-3 7.1,3.0,5.9,2.1,class-3 6.3,2.9,5.6,1.8,class-3 6.5,3.0,5.8,2.2,class-3 7.6,3.0,6.6,2.1,class-3 4.9,2.5,4.5,1.7,class-3 7.3,2.9,6.3,1.8,class-3 6.7,2.5,5.8,1.8,class-3 7.2,3.6,6.1,2.5,class-3 6.5,3.2,5.1,2.0,class-3 6.4,2.7,5.3,1.9,class-3 6.8,3.0,5.5,2.1,class-3 5.7,2.5,5.0,2.0,class-3 5.8,2.8,5.1,2.4,class-3 6.4,3.2,5.3,2.3,class-3 6.5,3.0,5.5,1.8,class-3 7.7,3.8,6.7,2.2,class-3 7.7,2.6,6.9,2.3,class-3 6.0,2.2,5.0,1.5,class-3 6.9,3.2,5.7,2.3,class-3 5.6,2.8,4.9,2.0,class-3 7.7,2.8,6.7,2.0,class-3 6.3,2.7,4.9,1.8,class-3 6.7,3.3,5.7,2.1,class-3 7.2,3.2,6.0,1.8,class-3 6.2,2.8,4.8,1.8,class-3 6.1,3.0,4.9,1.8,class-3 6.4,2.8,5.6,2.1,class-3 7.2,3.0,5.8,1.6,class-3 7.4,2.8,6.1,1.9,class-3 7.9,3.8,6.4,2.0,class-3 6.4,2.8,5.6,2.2,class-3 6.3,2.8,5.1,1.5,class-3 6.1,2.6,5.6,1.4,class-3 7.7,3.0,6.1,2.3,class-3 6.3,3.4,5.6,2.4,class-3 6.4,3.1,5.5,1.8,class-3 6.0,3.0,4.8,1.8,class-3 6.9,3.1,5.4,2.1,class-3

PLEASE SOLVE AS SOON AS POSSIBLE.