我在使用K-means聚类算法时遇到了一些麻烦。输入文件如下所示：
4
60 60
23 45
25 11
30 11
...
...
...
在60x60图像网格中共有4个聚类。该算法似乎有效，但当它重新开始重新计算质心并更改标签时，网格中的标签会慢慢开始变为1。经过大约5次迭代后，所有标签都变为1.我已经根据我的知识反复审查了代码，我无法弄清楚为什么所有标签都只变为1。任何帮助表示赞赏！
#include <iostream>
#include <fstream>
#include <cmath>
using namespace std;
class Node {
public:
int x;
int y;
int label;
double distace;
Node* next;
void printNode() {
cout << "X:\t" << x << endl;
cout << "Y:\t" << y << endl;
cout << "Label:\t" << label << endl;
}
Node(int i, int j) {
x = i;
y = j;
next = nullptr;
}
};
class LinkedList {
public:
Node* head;
int length;
Node* scanner;
LinkedList() {
Node* n = new Node(-999, -999);
head = n;
scanner = head;
length = 0;
}
void insert(Node* n) {
if (!head->next) {
head->next = n;
length++;
return;
}
n->next = head->next;
head->next = n;
length++;
}
void deleteNode(Node* n) {
Node* prev = head;
Node* current = head->next;
while (current) {
if (n->x == current->x &&
n->y == current->y &&
n->label == current->label) {
prev->next = current->next;
return;
}
prev = prev->next;
current = current->next;
}
length--;
}
void printList() {
Node* current = head->next;
while (current) {
current->printNode();
cout << endl;
current = current->next;
}
}
Node* scan() {
scanner = scanner->next;
if (!scanner) return 0;
return scanner;
}
void resetScanner() {
scanner = head;
}
void changeLabelTo(int x, int y, int newLabel) {
Node* current = head->next;
while (current) {
if (current->x == x &&
current->y == y) {
current->label = newLabel;
}
current = current->next;
}
}
};
class KMeans {
public:
struct xycoord {
int x;
int y;
};
int k;
xycoord* kcentroids;
LinkedList ll;
int row;
int col;
int** image;
int tracker;
int getLabel() {
int x = tracker++;
if (tracker > k) { tracker = 1; }
return x;
}
KMeans(int clusters, int r, int c) {
k = clusters;
tracker = 1;
kcentroids = new xycoord[k+1];
row = r;
col = c;
image = new int*[row];
for (int i = 0; i < row; i++)
image[i] = new int[col];
}
~KMeans() {
delete [] kcentroids;
for (int i = 0; i < row; i++)
delete [] image[i];
delete [] image;
cout << "Called!" << endl;
}
void displayImage() {
for (int i = 0; i < row; i++) {
for (int j = 0; j < col; j++) {
if (image[i][j] == 0) cout << " ";
else { cout << image[i][j]; }
}
cout << endl;
}
}
void imageOutput() {
for (int i = 0; i < ll.length; i++) {
Node* n = ll.scan();
if (n) {
image[n->x][n->y] = n->label;
}
}
displayImage();
}
void computeCentroids() {
for (int i = 1; i <= k; i++) {
kcentroids[i].x = 0;
kcentroids[i].y = 0;
}
int* count = new int[k+1];
for (int i = 0; i < ll.length; i++) {
Node* n = ll.scan();
if (n) {
kcentroids[n->label].x += n->x;
kcentroids[n->label].y += n->y;
count[n->label]++;
}
}
cout << endl;
for (int i = 1; i <= k; i++) {
kcentroids[i].x = kcentroids[i].x / count[i];
kcentroids[i].y = kcentroids[i].y / count[i];
/*
* i - label
* 6 - 4
* 7 - 3
* 8 - 2
* 9 - 1
*/
//image[kcentroids[i].x][kcentroids[i].y] = 10-i;
}
delete [] count;
}
void computeDistanceAndSetLabels() {
for (int i = 0; i < ll.length; i++) {
int minLabel = 0;
double min = 99999.0;
Node* n = ll.scan();
for (int j = 1; j <= k; j++) {
double m = 0.0;
// distance formula
m = sqrt(pow(n->x-kcentroids[j].x, 2) + pow(n->y-kcentroids[j].y,2));
if (m < min) {
min = m;
minLabel = j;
}
}
cout << i << " " << n->x << " " << n->y << " " << n->label << " ";
n->label = minLabel;
cout << minLabel << " " << n->label <<endl;
}
}
void startClustering() {
// more than 2 starts showing 1 take over all labels,
// this is to be changed to something better however
for (int i = 0; i < 4; i++) {
ll.resetScanner();
imageOutput();
ll.resetScanner();
computeCentroids();
ll.resetScanner();
computeDistanceAndSetLabels();
ll.resetScanner();
imageOutput();
}
}
};
Node* createNode(int x, int y, int k) {
Node* n = new Node(x, y);
n->label = k;
return n;
}
int main(int argc, char* argv[]) {
if (argc < 4) {
cout << "Please start program with: program in.txt out1.txt out2.txt" << endl;
return -1;
}
ifstream in(argv[1]);
if (!in) {
cout << "File: " << argv[1] << " could not be read" << endl;
return -2;
}
int k, rows, cols;
in >> k;
in >> rows;
in >> cols;
cout << k << " " << rows << " " << cols << endl;
KMeans km(k, rows, cols);
km.displayImage();
LinkedList ll;
int num;
while (in >> num) {
int num2;
in >> num2;
ll.insert(createNode(num, num2, km.getLabel()));
}
km.ll = ll;
km.ll.printList();
km.startClustering();
km.displayImage();
return 0;
}
答案 0 :(得分：1)
您未在computeCentroids（）中将计数初始化为零，从而导致未定义的行为。将它们与您的质心一起归零：
int* count = new int[k+1];
for (int i = 1; i <= k; i++) {
kcentroids[i].x = 0;
kcentroids[i].y = 0;
count[i] = 0;
}
当您按照以下方式新建数组时，也可以将零数组归零：
int* count = new int[k+1]();