朴素贝叶斯算法matlab实现

%------------------------------------------------------------
% NaiveBayesian Classification
%-----------------------------------------------------------
% Parameter:
%  k: Number of Cluster;

clear all
close all


k = 3;
attribute = 4;

%------------------------------------------------------
load iris_tr;
Y= IRIS_training_data;
clear IRIS_training_data
%---------------------------------------------------------
% Learning process
%------------------------------ Calculating  P（Ci）
[nrnc] = size（Y）;
for i= 1:1:k
    pc（i） = sum（Y（: attribute+i））/nr;
end
%--------------------------------------------------------------------
% Calculating Mean and Standard Error for each Class and Attribute 
%----------------------------------------------------------------------
for i = 1:1:k
    t = 1;
    for j = 1:1:nr
        if Y（j attribute+i） == 1
            x（t:） = Y（j 1:attribute）;
            t = t+1;
        end
    end
    mu（i:）  = mean（x）;
    xigma（i:） = std（x）;
    clear x
end
%-----------------------------------------------------------------
%----------------------------------------------------------------
% Testing process
%----------------------------------------------------------------
% Load test data set
%--------------------------------------------
load iris_te;
X= IRIS_testing_data;
clear IRIS_testing_data

% load iris_tr;
% X= IRIS