Hi Hasitha, Out of ensembling method available, following are the three main types that we are interested in:
- Stacking - Training multiple algorithms (called base-learners) on the same dataset, and combining them using another algorithm (meta-learner). - Bagging - Training a single algorithm over subsets of data. - Boosting - Training multiple algorithms on the same data, and combining them over a weighted average (giving higher priority to misclassified data points). You can do some background reading on those three topics to get a good understanding on ensembling methods. There are good online resources available. or if you can could you please provide me a time to a google hangout? Yes sure. Can you please set up a meeting? You can check my google calendar for free time slots. (I might not be available on 18-20 March) P.S: Don't call us sir, just call us by name :) Also, please CC "[email protected]" mailing list for all project related emails. Regards, Supun On Tue, Mar 15, 2016 at 1:36 AM, Hasitha Jayasundara < [email protected]> wrote: > Dear Sir, > > I have gone through the WSo2 ML algorithms(Linear Regression,Lasso > regression...)and now i have the idea about how the platform is > working.Since I am new to Ensembling and there's less resources for > learning Ensembling,can you provide me some resources or links to learn the > concept Ensembling,or if you can could you please provide me a time to a > google hangout?Thank you. > > On Tue, Mar 8, 2016 at 10:41 AM, Hasitha Jayasundara < > [email protected]> wrote: > >> Thank you very much sir.I 'll let you know if there's any issue. >> >> On Tue, Mar 8, 2016 at 10:03 AM, Supun Sethunga <[email protected]> wrote: >> >>> [looping dev] >>> >>> On Tue, Mar 8, 2016 at 10:01 AM, Supun Sethunga <[email protected]> wrote: >>> >>>> Hi Hasitha, >>>> >>>> Thank you for your interest in the above project. 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. >>>> >>>> To start with, you can get to know the Machine Learner product by >>>> downloading it and running it (Please use link [1] to download). Official >>>> documentation [2] and blog [3] will help you on how to use the product. As >>>> the next step, you can go through the source code of WSO2 ML ([4] and [5]), >>>> and get familiarized with the current implementations. >>>> >>>> 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] >>>> http://supunsetunga.blogspot.com/2015/09/building-your-first-predictive-model.html >>>> [4] https://github.com/wso2/carbon-ml >>>> [5] https://github.com/wso2/product-ml >>>> >>>> Regards, >>>> Supun >>>> >>>> On Tue, Mar 8, 2016 at 9:53 AM, Hasitha Jayasundara < >>>> [email protected]> wrote: >>>> >>>>> Dear Sir, >>>>> >>>>> I am an undergraduate of University of Moratuwa department of >>>>> Electronic and Telecommunication Engineering. I am very much interested in >>>>> machine learning knowledge and i would like to start the project' Ensemble >>>>> Methods Support for WSO2 Machine Learner'.So please provide me some guide >>>>> lines and materials for study and get a clear understanding about the >>>>> mentioned project. >>>>> >>>>> Thank you >>>>> >>>>> >>>> >>>> >>>> >>>> -- >>>> *Supun Sethunga* >>>> Software Engineer >>>> WSO2, Inc. >>>> http://wso2.com/ >>>> lean | enterprise | middleware >>>> Mobile : +94 716546324 >>>> >>> >>> >>> >>> -- >>> *Supun Sethunga* >>> Software Engineer >>> WSO2, Inc. >>> http://wso2.com/ >>> lean | enterprise | middleware >>> Mobile : +94 716546324 >>> >> >> > -- *Supun Sethunga* Software Engineer WSO2, Inc. http://wso2.com/ lean | enterprise | middleware Mobile : +94 716546324
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