資源簡介
c++實現k-mean算法#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <conio.h>
#include <math.h>
// FUNCTION PROTOTYPES
// DEFINES
#define SUCCESS 1
#define FAILURE 0
#define TRUE 1
#define FALSE 0
#define MA
代碼片段和文件信息
function?[features?targets?label]?=?k_means（train_features?train_targets?Nmu?region?plot_on）
%Reduce?the?number?of?data?points?using?the?k-means?algorithm
%Inputs:
% train_features -?Input?features
% train_targets -?Input?targets
% Nmu -?Number?of?output?data?points
% region -?Decision?region?vector:?[-x?x?-y?y?number_of_points]
%???plot_on?????????-?Plot?stages?of?the?algorithm
%
%Outputs
% features -?New?features
% targets -?New?targets
% label -?The?labels?given?for?each?of?the?original?features
if?（nargin?????plot_on?=?0;
end
[DL] =?size（train_features）;
dist =?zeros（NmuL）;
label?=?zeros（1L）;
%Initialize?the?mu‘s
mu =?randn（DNmu）;
mu =?sqrtm（cov（train_features‘1））*mu?+?mean（train_features‘）‘*ones（1Nmu）;
old_mu =?zeros（DNm?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件???????1833??2007-03-13?20:39??k_means.m
-----------?---------??----------?-----??----
?????????????????1833????????????????????1
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