Hi Anurag, Thank you for your interest in the above project. You can start by getting to know the Machine Learner product by downloading it and running it (Please use link [1] to download). Official documentation [2] will help you on using the product. You can find the source code base at [3] and [4]. As we have mentioned in the project proposal as well, the main objective is to integrate ensemble support for the existing flow of the WSO2 Machine Learner. We are focusing on the three methods: Bagging, Boosting and Stacking.
Please feel free to raise, if you have any questions or any unclear points. [1] http://wso2.com/products/machine-learner/ [2] https://docs.wso2.com/display/ML100/Introducing+Machine+Learner [3] https://github.com/wso2/carbon-ml [4] https://github.com/wso2/product-ml Regards, Supun On Sun, Mar 6, 2016 at 12:08 PM, Anurag Kashyap <anurag1...@gmail.com> wrote: > Hi Supun, > I'm currently working as a research assistant at NTU, Singapore for my > bachelor thesis in my final year, I looked at the list of GSoC projects > for WSO2 and I'm particularly interested in the project *Ensemble Methods > Support for WSO2 Machine Learner.* I am currently working on Ensemble > methods for multi-label classification, so I have some experience in this > field and I've read several scholarly articles about their implementation > and benefit. I believe I can contribute to this project as a GSoC intern. > Eagerly awaiting a response! > > Yours Sincerely, > *Anurag Kashyap* > *Research Assistant* > *Robotics-|| * > *Nanyang Technological University, Singapore* > > [image: Blog] <https://thelinuxkernel.wordpress.com> > -- *Supun Sethunga* Software Engineer WSO2, Inc. http://wso2.com/ lean | enterprise | middleware Mobile : +94 716546324
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