Hi Derek,
Thanks for taking the time to look into CDbw. This is the first time
anybody besides me has looked at it afaict and it is still quite
experimental. I agree with your analysis and have seen this occur
myself. It's a pathological case which is not handled well and your
proposed fix may in fact be the best solution.
On the std calculation itself, it is correct for scalar values of s0, s1
and s2 but I'm not as confident that it extrapolates to vectors. It also
has potential overflow, underflow and rounding issues but the running
sums method is convenient and is used throughout the clustering code via
AbstractCluster.computeParameters(). Most clustering doesn't really rely
on the std (Dirichlet does to compute pdf for Gaussian models) and this
is the only situation where I've seen this error.
Finally, checking the computeParameters() implementation, it does not
perform the std computation unless s0>1 so ignoring clusters with zero
or one point is probably the right thing to do. Does it fix the problems
you are seeing? I will write up a test today and commit a change if it does.
Jeff
On 9/21/10 10:39 AM, Derek O'Callaghan wrote:
Hi Jeff,
I've been trying out the CDbwDriver today, and I'm having a problem
running it on the clusters I've generated from my data, whereby I get
all 0s printed for the following lines in CDbwDriver.job():
System.out.println("CDbw = " + evaluator.getCDbw());
System.out.println("Intra-cluster density = " +
evaluator.intraClusterDensity());
System.out.println("Inter-cluster density = " +
evaluator.interClusterDensity());
System.out.println("Separation = " + evaluator.separation());
Stepping through this, I found a problem at these lines in
CDbwEvaluator.setStDev():
Vector std = s2.times(s0).minus(s1.times(s1)).assign(new
SquareRootFunction()).divide(s0);
double d = std.zSum() / std.size();
'd' was being set to NaN for one of my clusters, caused by
"s2.times(s0).minus(s1.times(s1))" returning a negative number, and so
the subsequent sqrt failed. Looking at the cluster which had the
problem, I saw that it only contained one point. However, 'repPts' in
setStDev() contained 3 points, in fact 3 copies of the same sole
cluster inhabitant point. This appeared to be causing the std
calculation to fail, I guess from floating point inaccuracies.
I then started digging back further to see why there were 3 copies of
the same point in 'repPts'. FYI I had specified numIterations = 2 to
CDbwMapper.runJob(). Stepping through the code, I see the following
happening:
- CDbwDriver.writeInitialState() writes out the cluster centroids to
"representatives-0", with this particular point in question being
written out as the representative for its cluster.
- CDbwMapper loads these into 'representativePoints' via
setup()/getRepresentativePoints()
- When CDbwMapper.map() is called with this point, it will be added to
'mostDistantPoints'
- CDbwReducer loads the mapper 'representativePoints' into
'referencePoints' via setup()/CDbwMapper.getRepresentativePoints()
- CDbwReducer writes out the same point twice, once by writing it out
as a most distant point in reduce(), and then again while writing it
out as a reference/representative point in cleanup()
- The process repeats, and an additional copy of the point is written
out by the reducer during each iteration, on top of those from the
previous iteration.
- Later on, the evaluator fails in the std calculation as described
above.
I'm wondering if the quickest solution would be to change the
following statement in CDbwDriver.writeInitialState():
if (!(cluster instanceof DirichletCluster) || ((DirichletCluster)
cluster).getTotalCount() > 0) {
to ignore clusters which only contain one point? The mapper would then
need to check if there was an entry for the cluster id key in
representative points before doing anything with the point.
Does the issue also point to a separate problem with the std
calculation, in that it's possible that negative numbers are passed to
sqrt()?
Thanks,
Derek
