%% Script file for Iris data (linear model)

load IrisData;  %Download this file from the class website

% The data:  X represents 150 flowers, each has 4 measurements (150 points
%            in R^4.
%            
%            Y represents the class as (1,0,0), (0,1,0), or (0,0,1), so Y
%            is also 150 x 3.

% Step 1:  Use Widrow-Hoff to train.  Some initial parameters to try:
% learning rate of 0.1, iterations to 500.  It is this portion you should
% change to get W, b




% Step 2:  Look at the errors in the classification.  The following code
% assumes that W is 3 x 4 and b is 3 x 1 (and you trained them in the
% previous section).  You should not have to change the code:

Confuse=zeros(3,3);
for j=1:150
    yout=W*X(j,:)'+b;
    Class(j,:)=(yout==max(yout));
    [val,idx1]=max(Class(j,:));
    [val,idx2]=max(Y(j,:));
    Confuse(idx2,idx1)=Confuse(idx2,idx1)+1;
end
Confuse=Confuse/50;