function [target,acc]= bayes( trainX,trainY,testX,testY )
% 朴素贝叶斯分类器
% target: 预测结果
% acc： 正确率
target=zeros(60,1);
acc=0;
% 把每个属性划均分为三段
for i=1:size(testX,1)
p1=1/3;
p2=1/3;
p3=1/3;
for j=1:4
s=testX(i,j);
mean = (max(trainX(:,j)) - min(trainX(:,j)))/3;
mean1 = min(trainX(:,j))+mean;
mean2=min(trainX(:,j))+2*mean;
if(s>mean2)
p1=p1*length(find(trainX(1:30,j)>mean2))/30;
p2=p2*length(find(trainX(31:60,j)>mean2))/30;
p3=p3*length(find(trainX(61:90,j)>mean2))/30;
end
if(s<mean1)
p1=p1*length(find(trainX(1:30,j)<mean1))/30;
p2=p2*length(find(trainX(31:60,j)<mean1))/30;
p3=p3*length(find(trainX(61:90,j)<mean1))/30;
end
if(s<=mean2&&s>=mean1)
p1=p1*(1-length(find(trainX(1:30,j)>mean2))/30-length(find(trainX(1:30,j)<mean1))/30);
p2=p2*(1-length(find(trainX(31:60,j)>mean2))/30-length(find(trainX(31:60,j)<mean1))/30);
p3=p3*(1-length(find(trainX(61:90,j)>mean2))/30-length(find(trainX(61:90,j)<mean1))/30);
end
end
if(p1>=p2&&p1>=p3)
target(i)=1;
end
if(p2>=p3&&p2>=p1)
target(i)=2;
end
if(p3>=p1&&p3>=p2)
target(i)=3;
end
if(target(i)==testY(i))
acc=acc+1;
end
end
acc=acc/60;
fprintf('test accuracy: %f%% \n',acc*100)
