算法来自于李航老师的《统计机器学习》
程序使用MATLAB2017A的版本，其中用到了字符串，低版本无法运行，请将字符串改为字符数组 clear;clc;close all %% 0. 导入数据 % 李航老师的《统计学习方法》第50页 data = ["1","1","1","1","1","2","2","2","2","2","3","3","3","3","3"; "S","M","M","S","S","S","M","M","L","L","L","M","M","L","L"; "-1","-1","1","1","-1","-1","-1","1","1","1","1","1","1","1","-1"]; X = num2cell(data(1:end - 1, :),2); Y = data(end, :); % 需要判断(2, 'S')的分类 X0 = ["2";"S"]; %% 1. 计算概率值， P = containers.Map; uY = unique(Y); for y = uY P(sprintf('P(Y=%s)',y)) = nnz(Y==y) / length(Y); for i = 1 : length(X) uX = unique(X{i}); for ux = uX P(sprintf('P(X(%d)=%s|Y=%s)',i,ux,y)) = nnz(X{i} == ux & Y == y) / nnz(Y == y); end end end % 显示概率数值 fprintf('*****************************************\n') for k = P.keys fprintf('%s = %s\n', k{1}, rats(P(k{:}))); end %% 2. 计算分类结果 rP = containers.Map; for y = uY rP(sprintf('P(X0=%s)',y)) = P(sprintf('P(Y=%s)',y)); for i = 1 : length(X0) rP(sprintf('P(X0=%s)',y)) = rP(sprintf('P(X0=%s)',y)) * P(sprintf('P(X(%d)=%s|Y=%s)',i,X0(i),y)); end end % 显示计算结果 fprintf('*****************************************\n') for k = rP.keys fprintf('%s = %s\n', k{1}, rats(rP(k{:}))); end %% 3. 选择概率最大的 fprintf('*****************************************\n') [~, idx] = max(cell2mat(rP.values)); allKeys = rP.keys; fprintf('%s\n', regexp(allKeys{idx}, '\(.*\)', 'match', 'once'));
计算结果如下：
