📄 k-均值聚类算法- 月华 - 新浪blog.htm
字号:
bestnum;<BR> double min=NUM_MAX;<BR> double
distant;</DIV>
<DIV>
kcluster=(ccLink)malloc(knum*sizeof(ccnode));</DIV>
<DIV> for
(i=0;i<knum;i++)<BR> {<BR> kcluster[i].data=(double*)malloc(row*sizeof(double));<BR> }<BR> <BR>
for (i=0;i<knum;i++)<BR> {<BR>
num=rand()%posnum; <BR> <BR>
for
(j=0;j<row;j++)<BR>
{<BR>
kcluster[i].data[j]=pos[num][j];<BR>
}<BR> <BR>
kcluster[i].dataindex = 0;<BR>
kcluster[i].next=NULL;<BR>
}<BR> for
(i=0;i<posnum;i++)<BR>
{<BR> min = NUM_MAX;<BR> for
(j=0;j<knum;j++)<BR>
{<BR>
distant=dist(pos[i],kcluster[j].data);<BR>
if
(distant<min)<BR>
{<BR>
min=distant;<BR>
bestnum=j;<BR>
}<BR> }<BR>
insertcluster(&kcluster[bestnum],pos[i],i);<BR>
numperclu[bestnum]++;//簇内数目加一<BR>
}<BR> for (i=0;i<knum;i++)<BR>
{<BR> calmean(&kcluster[i]);</DIV>
<DIV> }<BR> </DIV>
<DIV> return pos;<BR>}</DIV>
<DIV> </DIV>
<DIV>//删除不在同一个簇内的节点，并查入到最近的簇中<BR>void
delandinsercluster(double* data,int
bestnum)<BR>{<BR> int i;</DIV>
<DIV> for
(i=0;i<knum;i++)<BR> {<BR>
ccLink pointer;<BR> pointer =
&kcluster[i];<BR> ccLink
back=pointer;<BR>
pointer=pointer->next;</DIV>
<DIV> for (
;pointer!=NULL;pointer=pointer->next)<BR>
{<BR> <BR> if
(dist(data,pointer->data)<NUM_MIN)<BR> {<BR>
if
(i!=bestnum)<BR>
{<BR>
//查入到bestnum簇中<BR>
insertcluster(&kcluster[bestnum],data,pointer->dataindex);<BR>
numperclu[bestnum]++;//簇内数目加一</DIV>
<DIV>
//删除i簇中的节点，并查入到bestnum簇中<BR>
back->next=pointer->next;<BR>
free(pointer->data);<BR>
free(pointer);<BR>
numperclu[i]--;//簇内数目减一<BR> <BR>
}<BR>
break;<BR> }<BR> <BR> back
= pointer;<BR> }<BR> }</DIV>
<DIV><BR>}<BR>int kmeancluster(double**
pos)<BR>{ <BR> </DIV>
<DIV> int i,j;<BR> <BR> int
bestnum=0;<BR> double distance=0.0;<BR> for
(i=0;i<posnum;i++)<BR> {<BR> double
min=NUM_MAX;<BR> for
(j=0;j<knum;j++)<BR> {<BR> distance=dist(pos[i],kcluster[j].data);<BR>
if
(distance<min)<BR>
{<BR>
min=distance;<BR>
bestnum=j;<BR>
}<BR> <BR> }<BR>
delandinsercluster(pos[i],bestnum);<BR> <BR> }</DIV>
<DIV><BR> double**
temp=(double**)malloc(knum*sizeof(double*));<BR> for
(i=0;i<knum;i++)<BR> {<BR> temp[i]=(double*)malloc(row*sizeof(double));<BR> }</DIV>
<DIV> for
(i=0;i<knum;i++)<BR>
{<BR> for (j=0;j<row;j++)<BR>
{<BR>
temp[i][j]=kcluster[i].data[j];//后面的值<BR>
}<BR>
}<BR> </DIV>
<DIV> for
(i=0;i<knum;i++)<BR> {<BR> calmean(&kcluster[i]);<BR> }<BR> <BR>
int isstop = isexit(temp);</DIV>
<DIV><BR> for (i=0;i<knum;i++)<BR>
{<BR> free(temp[i]);<BR> }<BR>
free(temp);<BR> return isstop;</DIV>
<DIV> <BR>}<BR> <BR>void
printcluster()<BR>{<BR> ccLink
pointer;<BR> FILE* fp;<BR> if
((fp=fopen("out.txt","w"))==NULL)<BR> {<BR> printf("error!
can't open out
file!\n");<BR> exit(0);<BR> }<BR> <BR>
int i,j;<BR> for
(i=0;i<knum;i++)<BR>
{<BR> printf("第%d组:数目:%d节点:",i,numperclu[i]);<BR>
fprintf(fp,"%d %d
",i,numperclu[i]);<BR> for
(pointer=kcluster[i].next;pointer!=NULL;<BR> pointer=pointer->next )<BR>
{<BR> printf("%d
",pointer->dataindex);<BR>
fprintf(fp,"%d ",pointer->dataindex);</DIV>
<DIV>
}<BR>
printf("\n");<BR>
fprintf(fp,"\n");<BR> }<BR>
fclose(fp);<BR>}<BR>void
freeall()<BR>{<BR> free(numperclu);<BR>
int i;<BR> ccLink pointer;<BR>
ccLink
tpointer;<BR> for(i=0;i<knum;i++)<BR> {<BR> pointer=&kcluster[i];<BR> pointer=pointer->next;</DIV>
<DIV> while
(pointer!=NULL)<BR> {<BR> tpointer=pointer;<BR> pointer=pointer->next;<BR>
free(tpointer->data);<BR>
free(tpointer);<BR> }<BR>
free(kcluster[i].data); <BR> }<BR> <BR> free(kcluster);<BR>}<BR>int
main()<BR>{<BR> knum=3;</DIV>
<DIV> int i=0;<BR> double **pos
= initdata();<BR> </DIV>
<DIV> int
isstop=1;<BR> <BR> </DIV>
<DIV> while (isstop)<BR>
{<BR> i++;<BR>
isstop = kmeancluster(pos);<BR>
printf("第%d次迭代\n",i);<BR> <BR>
}<BR>
printcluster();<BR> <BR> freeall();</DIV>
<DIV> return
0;<BR>}</DIV></DIV></TD></TR></TBODY></TABLE>
<TABLE class=dashed cellSpacing=0 cellPadding=0 align=center
border=0>
<TBODY>
<TR>
<TD></TD></TR></TBODY></TABLE>
<TABLE class=function cellSpacing=0 cellPadding=0 align=center
border=0>
<TBODY>
<TR>
<TD><A title=提示：评论数每隔1~2小时刷新一次
onclick="hide('comment48e01819010003qp')"
href="javascript:;">评论(12)</A>┆<A
href="http://blog.sina.com.cn/control/writing/scriber/article_add_by_quote.php?blog_id=48e01819010003qp"
target=_blank>引用</A>┆<A title=提示：阅读数每隔1~2小时刷新一次
href="http://blog.sina.com.cn/myblog/article/article_reader.php?blog_id=48e01819010003qp"
target=_blank>阅读(487)</A>┆<A
href="http://blog.sina.com.cn/myblog/article/article_print.php?blog_id=48e01819010003qp"
target=_blank>打印</A></TD></TR></TBODY></TABLE></TD></TR></TBODY></TABLE>
<TABLE cellSpacing=0 cellPadding=0 align=center border=0>
<TBODY>
<TR>
<TD id=articleChild48e01819010003qp
style="DISPLAY: none"></TD></TR></TBODY></TABLE></DIV></CENTER><A
name=comment></A>
<CENTER>
<TABLE class=comment cellSpacing=0 cellPadding=0 border=0>
<TBODY>
<TR>
<TD>
<DIV id=comment48e01819010003qp>
<TABLE class="comment sysHand" cellSpacing=0 cellPadding=0
align=center>
<TBODY>
<TR class=title
onclick="hide('commentBody48e01819010003qp');swap('commentTitle48e01819010003qp','className','up','down');">
<TD class=up id=commentTitle48e01819010003qp>
<DIV class=sysBr500>文章评论</DIV></TD></TR></TBODY></TABLE>
<DIV id=commentBody48e01819010003qp>
<DIV class=alt>以下网友留言只代表其个人观点，不代表新浪网的观点或立场</DIV>
<DIV id=commentItem48e01819010003qp>
<TABLE class="sysHand item" cellSpacing=0 cellPadding=0
align=center>
<TBODY>
<TR class=iTitle
onclick="hide('commentItemBody48e01819010003qp1');swap('commentItemTitle48e01819010003qp1','className','iUp','iDown')">
<TD class=iUp id=commentItemTitle48e01819010003qp1>
<DIV class=sysBr500><A
href="http://blog.sina.com.cn/u/1222645785"><U>月华</U></A></DIV></TD></TR></TBODY></TABLE>
<DIV id=commentItemBody48e01819010003qp1>
<TABLE class=item cellSpacing=0 cellPadding=0 align=center>
<TBODY>
<TR>
<TD align=middle>
<TABLE class=itemBody cellSpacing=0 cellPadding=0
align=center border=0>
<TBODY>
<TR>
<TD class=iPubdate align=right>2006-05-23
20:15:37</TD></TR>
<TR>
<TD class=iText>
<DIV
class=sysBr476>k－均值是一种迭代的聚类算法，迭代过程中不断移动簇集中的成员直至到理想的簇集为止。利用k－均值得到的簇，簇中成员之间的相似的很高，同时不同簇中成员之间的相异度也很高。时间复杂度是o（tkn），t是迭代次数。找到的是局部最优解，而不是全局最优解。发现的仅是凸的簇，也不能很好的处理异常点。<BR>k－均值常用来和其它新算法做比较。<BR><BR>本人花了两个晚上编成，在p4机，512MRAM，2.82GHZ上运行，效率尚可。其中，读文件的程序可由不同的需要进行改写。由于时间仓卒，水平有限，错误之处，在所难免。欢迎批评指正。</DIV></TD></TR></TBODY></TABLE></TD></TR></TBODY></TABLE></DIV></DIV>
<TABLE class=item cellSpacing=0 cellPadding=0 align=center>
<TBODY>
<TR>
<TD class=iBottom></TD></TR></TBODY></TABLE>
⌨️ 快捷键说明
复制代码
Ctrl + C
搜索代码
Ctrl + F
全屏模式
F11
切换主题
Ctrl + Shift + D
显示快捷键
?
增大字号
Ctrl + =
减小字号
Ctrl + -