本文主要是介绍meanshift聚类的实现，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！
参见http://blog.csdn.net/u014568921/article/details/45197027
// meanshift-cluster.cpp : 定义控制台应用程序的入口点。
//#include "stdafx.h"
#include<iostream>
#include<vector>
#include<assert.h>
#include<cstdlib>
#include<time.h>
using namespace std;#define MSTYPE doubleclass meanshift
{
private:struct MSData{vector<MSTYPE>data;//unsigned int dim;MSData(unsigned int d){//dim = d;data.resize(d);}};vector<MSData>dataset;double kernel_bandwidth;MSData shiftvec(MSData vec){MSData shiftvector(vec.data.size());double total_weight = 0;for (int i = 0; i<dataset.size(); i++){MSData temp = dataset[i];double distance = euclidean_distance(vec, temp);double weight = gaussian_kernel(distance);for (int j = 0; j<shiftvector.data.size(); j++){shiftvector.data[j] += temp.data[j] * weight;}total_weight += weight;}for (int i = 0; i<shiftvector.data.size(); i++){shiftvector.data[i] /= total_weight;}return shiftvector;}double gaussian_kernel(double distance){double temp = exp(-(distance*distance) / (kernel_bandwidth));return temp;}double euclidean_distance(const MSData &data1, const MSData &data2){assert(data1.data.size() == data2.data.size());double sum = 0;for (int i = 0; i<data1.data.size(); i++){sum += (data1.data[i] - data2.data[i]) * (data1.data[i] - data2.data[i]);}return sqrt(sum);}public:meanshift(double kernel_bandwidth) :kernel_bandwidth(kernel_bandwidth){time_t t;srand(time(&t));}vector<MSData> apply(){vector<int> stop_moving;stop_moving.resize(dataset.size());vector<MSData> shifted_points = dataset;double max_shift_distance;do {max_shift_distance = 0;for (int i = 0; i<shifted_points.size(); i++){if (!stop_moving[i]) {MSData point_new = shiftvec(shifted_points[i]);double shift_distance = euclidean_distance(point_new, shifted_points[i]);if (shift_distance > max_shift_distance){max_shift_distance = shift_distance;}
#define EPSILON 0.00000001if (shift_distance <= EPSILON) {stop_moving[i] = 1;}shifted_points[i] = point_new;}}printf("max_shift_distance: %f\n", max_shift_distance);} while (max_shift_distance > EPSILON);for (int i = 0; i < dataset.size(); i++){cout << "原始坐标 （" << dataset[i].data[0] << "，" << dataset[i].data[1] << "） 滑动到 （"<< shifted_points[i].data[0] << "，" << shifted_points[i].data[1] << "）" << endl;}return shifted_points;}void generatedata(int datanums,vector<int>&span){for (int i = 0; i < datanums; i++){MSData dd(span.size());for (int j = 0; j < span.size(); j++){dd.data[j] = double(rand()) / (RAND_MAX + 1.0)*span[j];}dataset.push_back(dd);}}};int _tmain(int argc, _TCHAR* argv[])
{meanshift ms(4);vector<int>span;span.push_back(20);span.push_back(20);ms.generatedata(100, span);ms.apply();return 0;
}
结果如下图
这篇关于meanshift聚类的实现的文章就介绍到这儿，希望我们推荐的文章对编程师们有所帮助！
