%
% Examples 9.14
% 
% Written by:
% -- 
% John L. Weatherwax                2008-02-20
% 
% email: wax@alum.mit.edu
% 
% Please send comments and especially bug reports to the
% above email address.
% 
%-----

clear all; 
close all; 
clc; 

addpath('../../Code/CSTool');
load household; 

nPts = 20; 

% attach classlabels to each group: 
men(:,end+1) = 1; women(:,end+1) = 2; 

% lump everything into one data matrix: 
X = [men; women]; 

% standardize the data and append the class labels back: 
if( 1 ) 
  Xc = zscore(X(:,1:4)); 
  Xp = [Xc,X(:,end)];
  X  = Xp;
end

% grow a tree with all of the data: 
pies = [0.5, 0.5];
maxn = 1; % <- the maximum number of elements we will allow in each leaf
clas = 1:2;
Nk = [20,20];
tree = csgrowc(X,maxn,clas,Nk,pies); 
csplotreec(tree);
saveas( gcf, 'prob_9_3_tree', 'epsc' ); 

% from the csplottree we get only TWO branches with a split point at x2_sp
x2_sp = -0.42;
%x2_sp = 2.7e2; 
indWP = find( X(:,2)<x2_sp );
indMP = find( X(:,2)>=x2_sp );

pcc = (sum(X(indMP,5)==1) + sum(X(indWP,5)==2))/40;
fprintf('prob. correct classification = %10.5f\n',pcc');