On Tue, Feb 16, 2010 at 10:25 PM, Jeff Eastman
<j...@windwardsolutions.com>wrote:
> Looks to me like the unit tests are the only calls to recomputeCenter,
> which is where the center is set. The clusterer seems to be calling
> computeCentroid, which sets the centroid, instead. I'm not sure why it needs
> both instance variables, as the pointProbSum and weightedPointTotal
> variables take the place of the single pointTotal in ClusterBase. I think
> perhaps center and centroid need to be merged?
>
> In k-means and canopy, the center is the (read-only) current centroid which
> is used for the distance calculations during an iteration, and it is
> recomputed by computeCentroid (using pointTotal and numPoints) at the end of
> the iteration.
>
> So just writing computeCentroid should do right? Which is what its doing.
@Override
public void write(DataOutput out) throws IOException {
out.writeInt(clusterId);
out.writeBoolean(converged);
Vector vector = computeCentroid();
VectorWritable.writeVector(out, vector);
}
@Override
public void readFields(DataInput in) throws IOException {
clusterId = in.readInt();
converged = in.readBoolean();
VectorWritable temp = new VectorWritable();
temp.readFields(in);
setCenter(temp.get());
this.pointProbSum = 0;
this.weightedPointTotal = getCenter().like();
}
Jeff
>
>
>
> Robin Anil wrote:
>
>> I have been trying to convert FuzzyKMeans SoftCluster(which should be
>> ideally be named FuzzyKmeansCluster) to use the ClusterBase.
>>
>> I am getting* the same center* for all the clusters. To aid the conversion
>> all i did was remove the center vector from the SoftCluster class and
>> reuse
>> the same from the ClusterBase. These are essentially making no change in
>> the
>> tests which passes correctly.
>>
>> So I am questioning whether the implementation keeps the average center at
>> all ? Anyone who has used FuzzyKMeans experiencing this?
>>
>>
>> Robin
>>
>>
>>
>
>
