[ https://issues.apache.org/jira/browse/MATH-817?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13495744#comment-13495744 ]
Jared Becksfort commented on MATH-817:
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I like the idea of allowing the use of public functions after initialization to alleviate some of the constructor mess. However, it is a pretty typical use case to provide initial guesses for the means without providing initial guesses for the weights or covariance matrices, or sometimes providing just covariance matrices. For cases such as that, it seems to me that the methods you describe above would also need to be overloaded a few different ways to accommodate that.
If we are already going to break out the fit function to a public member that accepts data, then I think it may be OK and make for a clearer API to have some public members allowing specification of various initial estimates. A method called setInitialMeans(double[][] initialMeans) could be used if initial guesses are used, otherwise it will be estimated from the data. There would be 2 other similar methods for weights and covariance matrices. We could also have one that accepts a mixture model for the initial guesses.
> 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: AbstractMultivariateRealDistribution.java.patch, MixtureMultivariateRealDistribution.java.patch, MultivariateNormalDistribution.java.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.
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