detreeexp45.m

支持向量机工具箱

global data textdata

global grpnum node grpname tree
 
global cost secost ntermnodes bestlevel
% 计算分类代价
resubcost = treetest(tree,'resub');
[cost,secost,ntermnodes,bestlevel] = treetest(tree,'cross',data(:,1:2), textdata(:,1));
plot(ntermnodes,cost,'b-', ntermnodes,resubcost,'r--')
figure(gcf);
xlabel('叶结点数量');
ylabel('代价 (错误分类误差)');
legend('交叉确认法','回代法');
%% Which tree should we choose? A simple rule would be to choose the tree with the smallest cross-validation error.
% While this may be satisfactory, we might prefer to use a simpler tree if it is roughly as good as a more complex tree. 
% The rule we will use is to take the simplest tree that is within one standard error of the minimum. 
% That's the default rule used by the TREETEST function.

[mincost,minloc] = min(cost);
cutoff = mincost + secost(minloc);
hold on
plot([0 20], [cutoff cutoff], 'k:')
plot(ntermnodes(bestlevel+1), cost(bestlevel+1), 'mo')
legend('交叉确认法','回代法','最小代价＋一个标准误差.','最佳选择')
hold off