Part 4: Creating Personalised Data

To answer some of the questions in this coursework you will need to create a test dataset that is unique to you. As the answers you get will depend on the test set you use, you must ensure that you generate the test set correctly, otherwise your answers will be wrong!

To create this test set, Xtest, use your 7-digit KCL student ID (this is the number that appears on your College ID card, it is NOT the k-number you use to log-into College computers).

Define s1, s2, s3, s4, s5, s6, s7 to be the 1st to 7th digits of your KCL student ID number, then define Xtest using the following MATLAB code:

Stest=[s1, s2, s3, s4, s5, s6, s7; s2, s3, s4, s5, s6, s7, s1; s3, s4, s5, s6, s7, s1, s2; s4, s5, s6, s7, s1, s2, s3]; Stest=bsxfun(@rdivide,Stest,[2.3;4;1.5;4]); Xtest=bsxfun(@plus,Stest,[4;2;1;0]);

Hence, if your KCL student ID was 1234567, Xtest would be:

4.4348 4.8696 5.3043 5.7391 6.1739 6.6087 7.0435 2.5000 2.7500 3.0000 3.2500 3.5000 3.7500 2.2500 3.0000 3.6667 4.3333 5.0000 5.6667 1.6667 2.3333 1.0000 1.2500 1.5000 1.7500 0.2500 0.5000 0.7500

Each column of Xtest is a sample taken from a 4-dimensional feature-space.

In your report give your 7-digit KCL student ID, and report the values in the array Xtest.

Part 5: Neural Networks

Assessed Exercise

Answer tutorial question 6 in the section of the tutorial on Neural Networks, except use values of θ = −s3, w1 = −s4, and w2 = s5 as the initial parameter values, where s3, s4, and s5, are the third, fourth and fifth digits of your 7-digit KCL student ID. Continue to perform iterations of the algorithm until convergence to a solution or until 12 iterations have been performed, whichever is earliest.

This question is about using the Sequential Delta Learning Algorithm to find the weights of a Linear Threshold Unit to classify the same data as was used in Part 3 of Assignment 1. You can do this manually, but it is laborious and error-prone. It will be easier for you to write some simple code to do this for you.