Hi Rahul, Thanks for the reply!
I am working on implementing Gaussian Mixture Model assuming that the co-variance matrix is same for all the Gaussians. The JIRA which deals GMM is MADBLIB-410: https://issues.apache.org/jira/browse/MADLIB-410?jql=project%20%3D%20MADLIB Can this be assigned to me, or how do I get it assigned to me? Thanks, Aditya On Mon, Mar 21, 2016 at 3:41 PM, Rahul Iyer <ri...@pivotal.io> wrote: > Hi Aditya, > > Welcome to the MADlib community! > > Gaussian Mixture models is extrememly useful and we would heartily welcome > a contribution for it. The SQLEM paper might be oversimplifying the > capabilities of the database (e.g. assuming there is no array type is > unnecessary for Postgresql). You could speed things (both dev time and > execution time) by writing some of the functions in C++. K-means is an > example of how clustering is implemented. > IMO, assuming the same covariance matrix is reasonable. We could extend the > capabilities after the initial implementation is complete. > > There was some work started a long time ago that built perceptrons using > the convex framework (link <https://github.com/iyerr3/madlib/tree/mlp>). > There are still some bugs in that code since the trained network isn't > converging. You could start there or build a new module - either ways an > MLP module is frequently demanded by the data science community. > > I would suggest starting with Gaussian mixtures and then moving to > perceptrons if GMM work is completed. > > Feel free to ask questions on this forum. Looking forward to collaborating > with you. > > Best, > Rahul > > On Thu, Mar 17, 2016 at 2:08 PM, Aditya Nain <adityana...@gmail.com> > wrote: > > > Hi, > > > > My name is Aditya Nain, and I am a graduate student at University of > > Florida. > > I have been learning MADLib for a while and want to contribute to MADLib. > > I went through some of the open stories in JIRA and started working on > > MADLIB-410 : > > > > > https://issues.apache.org/jira/browse/MADLIB-410?jql=project%20%3D%20MADLIB > > > > which is about implementing Gaussian Mixture Model using Expectation > > Maximization (EM) algorithm. > > > > I came across the following paper while searching for distributed EM > > algorithm which can be implemented in MADLib. > > > > Carlos Ordonez, Paul Cereghini "SQLEM: fast clustering in SQL using the > EM > > algorithm" ACM SIGMOD Record, Volume 29 Issue 2, June 2000 Pages 559-570. > > http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.28.7564 > > > > I thought of implementing the approach discussed in the paper, but the > > paper makes an assumption that the covariance martix is the same for all > > the clusters ( i.e covariance matrix is same for all the Gaussian > > distributions). So, I wanted to know the opinion of the community if it's > > fine to go with the assumption made in the paper and implement it in > > MADLib. > > > > Also, currently MADLib doesn't have an implementation of a perceptron, > nor > > did I find any open story related to it in JIRA. I came across the > > following paper, which talks about a distributed algorithm for > perceptron : > > > > Ryan McDonald, Keith Hall, Gideon Mann "Distributed training strategies > for > > the structured perceptron" > > http://dl.acm.org/citation.cfm?id=1858068 > > > > Would it useful to have a distributed implementaion of perceptron in > > MADlib? > > > > Thanks, > > Aditya > > >
