1) Convert the table into format convenient for the processing with MATLAB.

2) Prepare a program that perform K Nearest Neighbours algorithm using Euclidian distance. (Your program should not utilise the MATLAB function for KNN)

3) For each row (instance) from the table prepare the results of the cross-validation: for each instance apply the program for different values of K = 1,2,3,4,5. Analyse the accuracy of the classification using cross-validation and visualize your results.

4) Please create a decision tree for prediction of USA presidential elections. Select randomly several example of each class for the test set and exclude them from the training set. Find the training and the test set errors.

5) Which method works better for this dataset? Explain please.

6) Please write a conclusion.