[
https://issues.apache.org/jira/browse/MATH-817?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13610378#comment-13610378
]
Jared Becksfort commented on MATH-817:
--------------------------------------
{quote}
Looking at the javadoc, it seems this implementation is based on CRAN mixtools.
{quote}
I don't consider it to be an implementation of Mixtools. The implementation is
directly based on an algorithm listed in EM Demystified.
See page 13 of
https://www.ee.washington.edu/techsite/.../UWEETR-2010-0002.pdf
I used Mixtools to verify the results. I initially was going to have a similar
API to it, but now the APIs are no longer related. One area where I got an
idea from them is in estimateMultivariateNormalMixtureModelDistribution. They
sort the initial data by mean, and so do I. I don't know that that qualifies
it as a derived work or implementation, as lots of algorithms base initial
clustering by vector means.
Perhaps I am overgenerous with credit to Mixtools in the javadocs. Don't get me
wrong, I think it is a very useful R package. It was the tool I used before I
decided I needed the algorithm directly in Java and that Weka EM
fitting/clustering would not suffice. When developing the code, I used
Mixtools to verify the results. I did look at how they initialized the mixture
when no weights, means, or covariances were supplied, but I don't think they
can claim a monopoly on binning data by mean.
Jared
> Multivariate Normal Mixture Model Fitting by Expectation Maximization
> ---------------------------------------------------------------------
>
> Key: MATH-817
> URL: https://issues.apache.org/jira/browse/MATH-817
> Project: Commons Math
> Issue Type: New Feature
> Reporter: Jared Becksfort
> Priority: Minor
> Attachments: math_817.patch,
> MultivariateNormalMixtureExpectationMaximizationFitter.java,
> MultivariateNormalMixtureExpectationMaximizationFitterTest.java
>
> Original Estimate: 1m
> Remaining Estimate: 1m
>
> I will submit a class for fitting Multivariate Normal Mixture Models using
> Expectation Maximization.
> > Hello,
> >
> > I have implemented some classes for multivariate Normal distributions,
> > multivariate normal mixture models, and an expectation maximization fitting
> > class for the mixture model. I would like to submit it to Apache Commons
> > Math. I still have some touching up to do so that they fit the style
> > guidelines and implement the correct interfaces. Before I do so, I thought
> > I would at least ask if the developers of the project are interested in me
> > submitting them.
> >
> > Thanks,
> > Jared Becksfort
> Dear Jared,
> Yes, that would be very nice to have such an addition! Remember to also
> include unit tests (refer to the current ones for examples). The best would
> be to split a submission up into multiple minor ones, each covering a natural
> submission (e.g. multivariate Normal distribution in one submission), and
> create an issue as described at
> http://commons.apache.org/math/issue-tracking.html .
> If you run into any problems, please do not hesitate to ask on this mailing
> list.
> Cheers, Mikkel.
--
This message is automatically generated by JIRA.
If you think it was sent incorrectly, please contact your JIRA administrators
For more information on JIRA, see: http://www.atlassian.com/software/jira
