%%% Boxplots of iris data

load iris_data.data
iris = iris_data

% Transform the data so that each column has samples with one class label
% We will only use the first feature from the original data

iris2 = ones(50,3);
iris2(:,1) = iris(iris(:,5)==0, 1);
iris2(:,2) = iris(iris(:,5)==1, 1);
iris2(:,3) = iris(iris(:,5)==2, 1);

boxplot(iris2);



%%% Scatterplot of voting data

load house-votes.data
votes = house_votes;

% Keep only the political party column and a column corresponding to one issue
votes2 = ones(435,2);
votes2(:,1) = votes(:,1);
votes2(:,2) = votes(:,6);

% Add Gaussian noise
jitter = randn(size(votes2))/10;
votes3 = votes2 + jitter;

% Plot
scatter(votes3(:,1),votes3(:,2),'.');
axis([-1 2 -1.5 1.5]);
