Calculate the training error of your classifier, that is over the whole training set.

Rules • Use basic Python, numpy and matplotlib modules. Any other modules need my approval.

• Produce a LATEX-generated PDF of your report.

• Ask plenty of questions to ensure you have a good understanding of the project. • The code (and reports) should look vastly different for different groups. Very similar code will incur a hefty penalty.

• Everyone should participate…no excuses, no exceptions.

In this project we use pattern recognition to determine whether a subject is relaxed or planning. In this study EEG data was collected from patients in each of these two states. We build a classifier to help make automated decisions.

Part 1

1. Study the dataset located here: https://archive.ics.uci.edu/ml/datasets/Planning+Relax. You will note that there are 182 training patterns of 2 classes with the last column being the class label.

2. Write code to produce produce the posterior probability P (C1|x)

3. Calculate the training error of your classifier, that is over the whole training set.

Part 2