The following is a JSP code for K-MEANS CLUSTERING .... My proect , titled "Pattern Analysis of Web Usage for System Improvement", involves the web log info from a database and then considering the attributes IP address and WEBPAGES,IN THE FORM OF NUMBERS(X,Y) for K-MEANS CLUSTERING... the output of this is used for WEB CACHE REPLACEMENT.. please let me knw,if the following code of K-MEANS CLUSTERING in JSP is proper and will take 2 dimenshional input(ip,webpages)... i m having hard time in converting ip and webpages into number for K-MEANS CLUSTERING...please reply.
<html>
<head>
<script type="text/javascript">
function kmeans( arrayToProcess, Clusters )
{
var Groups = new Array();
var Centroids = new Array();
var oldCentroids = new Array();
var changed = false;
// order the input array
arrayToProcess.sort(function(a,b){return a - b})
// initialise group arrays
for( initGroups=0; initGroups < Clusters; initGroups++ )
{
Groups[initGroups] = new Array();
}
// pick initial centroids
initialCentroids=Math.round( arrayToProcess.length/(Clusters+1) );
for( i=0; i<Clusters; i++ )
{
Centroids[i]=arrayToProcess[ (initialCentroids*(i+1)) ];
}
do
{
for( j=0; j<Clusters; j++ )
{
Groups[j] = [];
}
changed=false;
for( i=0; i<arrayToProcess.length; i++ )
{
Distance=-1;
oldDistance=-1
for( j=0; j<Clusters; j++ )
{
distance = Math.abs( Centroids[j]-arrayToProcess[i] );
if ( oldDistance==-1 )
{
oldDistance = distance;
newGroup = j;
}
else if ( distance <= oldDistance )
{
newGroup=j;
oldDistance = distance;
}
}
Groups[newGroup].push( arrayToProcess[i] );
}
oldCentroids=Centroids;
for ( j=0; j<Clusters; j++ )
{
total=0;
newCentroid=0;
for( i=0; i<Groups[j].length; i++ )
{
total+=Groups[j][i];
}
newCentroid=total/Groups[newGroup].length;
Centroids[j]=newCentroid;
}
for( j=0; j<Clusters; j++ )
{
if ( Centroids[j]!=oldCentroids[j] )
{
changed=true;
}
}
}
while( changed==true );
return Groups;
}
</script>
</head>
<html>
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