kNN算法c语言实现

#include
#include
#include
#include

#define K 10 //kNN中选取最近邻居的个数
#define LINE 1024 //每个文件字符数

const char *to_search_train = "F:\\kNN\\train\\*.txt"; //train数据地址
const char *to_search_test = "F:\\kNN\\test\\*.txt"; //test数据地址

struct //定义结构体 储存train数据和标签
{
int train_mat[2000][LINE]; //矩阵每一行都是1*LINE的矩阵
int train_label[2000]; //储存每个数据的标签

}Train;

struct //定义结构体 储存test数据和标签
{
int test_mat[2000][LINE];
int test_label[2000];

}Test;

float mat_dist[1000][2000]; //定义距离矩阵，储存每个test数据到每个train数据的距离

//定义子函数，功能：将每个test数据与所有train数据的距离进行排序，选取距离最小的前K个，这K个数据标签类型最多的，将此标签返回给主函数
int BubbleSort(float mat_dist_row[], int label[],int num_train)
{
int i,j,k;
int temp,temp_label;
int num[K] = {0};
int max = 0;
int label_final = 0;

for(i = 0;i < num_train;i++) //冒泡排序，距离从小到大，同时将label对应跟随
{
for(j = i+1;j < num_train;j++)
{
if(mat_dist_row[i] > mat_dist_row[j])
{
temp = mat_dist_row[i];
mat_dist_row[i] = mat_dist_row[j];
mat_dist_row[j] = temp;

temp_label = label[i];
label[i] = label[j];
label[j] = temp_label;
}
}
}

for (k = 0;k < K;k++) //统计前K个数据，各种标签的个数
{
switch(label[k])
{
case 0: num[0]++;break;
case 1: num[1]++;break;
case 2: num[2]++;break;
case 3: num[3]++;break;
case 4: num[4]++;break;
case 5: num[5]++;break;
case 6: num[6]++;break;
case 7: num[7]++;break;
case 8: num[8]++;break;
case 9: num[9]++;break;
default: break;
}
}

max = num[0];

for(i = 0;i < K;i++) //标签类型最多的，选择次标签
{
if (num[i] > max )
{
max = num[i];
label_final = i;
}
}
return label_final;
}


int main()
{

FILE *fp;
int c; //用于逐个读入字符数据
int train_i = 0,train_j = 0,test_i = 0,test_j = 0; //用于循环
int count_train = 0,count_test = 0; //用于统计train和test文件的个数
int i,j,k,l; //用于循环
int sum = 0; //距离求和
int update_label[2000]; //每次调用函数，更新label
int classifier; //记录返回的标签类型
int count = 0; //错误的个数
float rate; //错误率

char str_adr[255]; //fopen函数读入文件名时地址

long handle; //用于查找的句柄
struct _finddata_t fileinfo; //文件信息的结构体


handle = _findfirst(to_search_train,&fileinfo); //第一次查找
sprintf(str_adr, "F:\\kNN\\train\\%s", ); //文件名赋给str_adr

if(-1 == handle)
{
printf("File not exit\n");
}
else
{
switch([0]) //给第一个文件赋予标签
{
case '0': Train.train_label[count_train] = 0;break;
case '1': Train.train_label[count_train] = 1;break;
case '2': Train.train_label[count_train] = 2;break;
case '3': Train.train_label[count_train] = 3;break;
case '4': Train.train_label[count_train] = 4;break;
case '5': Train.train_label[count_train] = 5;break;
case '6': Train.train_label[count_train] = 6;break;
case '7': Train.train_label[count_train] = 7;break;
case '8': Train.train_label[count_train] = 8;break;
case '9': Train.train_label[count_train] = 9;break;
default: break;
}

count_train++;

if((fp = fopen(str_adr,"r")) == NULL)
printf("Error!Can't open the file!\n");

else //将文件中'0'和'1'字符转化为数字0，1，并储存
{
while((c = fgetc(fp)) != EOF)
{
if(c == '0' || c == '1')
{
Train.train_mat[train_i][train_j] = c - '0';
train_j++;
}
}
}

fclose(fp);

while(!_findnext(handle,&fileinfo)) //循环查找其他符合的文件，知道找不到其他的为止
{

train_j = 0;
train_i++;

sprintf(str_adr, "F:\\kNN\\train\\%s", );

switch([0]) //给后面文件赋予标签
{
case '0': Train.train_label[count_train] = 0;break;
case '1': Train.train_label[count_train] = 1;break;
case '2': Train.train_label[count_train] = 2;break;
case '3': Train.train_label[count_train] = 3;break;
case '4': Train.train_label[count_train] = 4;break;
case '5': Train.train_label[count_train] = 5;break;
case '6': Train.train_label[count_train] = 6;break;
case '7': Train.train_label[count_train] = 7;break;
case '8': Train.train_label[count_train] = 8;break;
case '9': Train.train_label[count_train] = 9;break;
default: break;
}
if((fp = fopen(str_adr,"r")) == NULL)
printf("Error!Can't open the file!\n");
else //将文件中'0'和'1'字符转化为数字0，1，并储存
{
while((c = fgetc(fp)) != EOF)
{
if(c == '0' || c == '1')
{
Train.train_mat[train_i][train_j] = c - '0';
train_j++;
}
}
}

count_train++;
fclose(fp);
}
}
_findclose(handle);


//下面重复上面文件读入和储存的过程，读入并储存所有test数据
handle = _findfirst(to_search_test,&fileinfo);
sprintf(str_adr, "F:\\kNN\\test\\%s", );

if(

-1 == handle)
{
printf("File not exit\n");
}
else
{
switch([0])
{
case '0': {Test.test_label[count_test] = 0;break;}
case '1': {Test.test_label[count_test] = 1;break;}
case '2': {Test.test_label[count_test] = 2;break;}
case '3': {Test.test_label[count_test] = 3;break;}
case '4': {Test.test_label[count_test] = 4;break;}
case '5': {Test.test_label[count_test] = 5;break;}
case '6': {Test.test_label[count_test] = 6;break;}
case '7': {Test.test_label[count_test] = 7;break;}
case '8': {Test.test_label[count_test] = 8;break;}
case '9': {Test.test_label[count_test] = 9;break;}
default: break;
}

count_test++;

if((fp = fopen(str_adr,"r")) == NULL)
printf("Error!Can't open the file!\n");

else
{
while((c = fgetc(fp)) != EOF)
{
if(c == '0' || c == '1')
{
Test.test_mat[test_i][test_j] = c - '0';
test_j++;
}
}
}

fclose(fp);

while(!_findnext(handle,&fileinfo))
{

test_j = 0;
test_i++;
sprintf(str_adr, "F:\\kNN\\test\\%s", );

switch([0])
{
case '0': {Test.test_label[count_test] = 0;break;}
case '1': {Test.test_label[count_test] = 1;break;}
case '2': {Test.test_label[count_test] = 2;break;}
case '3': {Test.test_label[count_test] = 3;break;}
case '4': {Test.test_label[count_test] = 4;break;}
case '5': {Test.test_label[count_test] = 5;break;}
case '6': {Test.test_label[count_test] = 6;break;}
case '7': {Test.test_label[count_test] = 7;break;}
case '8': {Test.test_label[count_test] = 8;break;}
case '9': {Test.test_label[count_test] = 9;break;}
default: break;
}
if((fp = fopen(str_adr,"r")) == NULL)
printf("Error!Can't open the file!\n");
else
{
while((c = fgetc(fp)) != EOF)
{
if(c == '0' || c == '1')
{
Test.test_mat[test_i][test_j] = c - '0';
test_j++;
}
}
}

count_test++;
fclose(fp);
}
}
_findclose(handle);

for (i = 0;i < count_test;i++) //计算每个test(循环中的i)数据到每个train(循环中的j)数据的距离
{
for (j = 0;j < count_train;j++)
{
for (k = 0;k < LINE;k++)
{
sum =sum + (Test.test_mat[i][k]-Train.train_mat[j][k])*(Test.test_mat[i][k]-Train.train_mat[j][k]);
}
mat_dist[i][j] = sqrt(sum);
sum = 0;
}

for (l = 0;l < count_train;l++) //更新train数据的label
{
update_label[l] = Train.train_label[l];
}

classifier = BubbleSort(mat_dist[i],update_label,count_train);//调用子函数，得到第i个test数据的标签

if (Test.test_label[i] != classifier) //统计错误个数
{
count++;
}
printf("the real answer is: %d, the classififier is: %d\n",Test.test_label[i],classifier);//打印
}
rate = (float)count/count_test; //计算

错误率
printf("the total number of errors is: %d\n",count); //打印
printf("the total error rate is: %f\n",rate);

return 0;
}