Hi Anurag, Have you started on the project proposal? If so, could you please share it (the draft) with us?
Thanks, On Mon, Mar 21, 2016 at 10:03 AM, Nirmal Fernando <nir...@wso2.com> wrote: > > > On Mon, Mar 21, 2016 at 10:01 AM, Supun Sethunga <sup...@wso2.com> wrote: > >> Hi Anurag, >> >> Can you help me figure out the significance of the serialVersionUID field? >> >> >> All the algorithm classes including the one you mentioned implement the >> Serializable interface (Because these generated models can be exported and >> imported as java objects). "serialVersionUID" is used when serializing >> and deserializing the objects. If we do not define a "serialVersionUID", >> then java runtime will generate them during serialization and >> deserialization. And if these two serialVersionUID's does not matches, >> then the deserialization fails. As a result, the java object will not be >> readable. You can check [1] for further details. >> >> Also, I wanted to know if I should include personal details too in the >>> proposal- such as my university and where I'm currently working. >> >> You may include. You can check out a sample gsoc proposal by Nirmal ( >> nir...@wso2.com) at [2]. >> >> BTW, please CC to WSO2 Developers mailing list (dev@wso2.org) for all >> project-related discussions. >> > > You may have to subscribe to dev@, please refer to http://wso2.com/mail/ > >> >> [1] >> http://javarevisited.blogspot.com/2014/05/why-use-serialversionuid-inside-serializable-class-in-java.html >> [2] http://nirmalfdo.blogspot.com/search/label/GSoC-2011 >> >> Regards >> Supun >> >> >> On Thu, Mar 17, 2016 at 6:26 PM, Anurag Kashyap <anurag1...@gmail.com> >> wrote: >> >>> Hi Supun, >>> I was going through this >>> <https://github.com/wso2/carbon-ml/blob/master/components/ml/org.wso2.carbon.ml.core/src/main/java/org/wso2/carbon/ml/core/spark/algorithms/RidgeRegression.java> >>> link. Can you help me figure out the significance of the serialVersionUID >>> field? If that field is necessary then anonymous classes will have to be >>> implemented instead of lambda expressions in several places. Also, I wanted >>> to know if I should include personal details too in the proposal- such as >>> my university and where I'm currently working. >>> >>> >>> >>> >>> >>> >>> >>> On Mon, Mar 14, 2016 at 5:57 PM, Supun Sethunga <sup...@wso2.com> wrote: >>> >>>> Hi Anurag, >>>> >>>> Yes, the master branch is using java 8, hence you can use lambda >>>> expressions. >>>> >>>> Regards, >>>> Supun >>>> >>>> On Mon, Mar 14, 2016 at 3:24 PM, Anurag Kashyap <anurag1...@gmail.com> >>>> wrote: >>>> >>>>> Hi Supun, >>>>> One more question. I couldn't find if the version of Java being used >>>>> is Java 8 or a previous version. If it is Java 8, Lambda calculus can be >>>>> used to make some things easier, especially while working with spark. >>>>> Thanks and Regards, >>>>> Anurag Kashyap >>>>> >>>>> >>>>> On Mon, Mar 7, 2016 at 8:05 PM, Supun Sethunga <sup...@wso2.com> >>>>> wrote: >>>>> >>>>>> [Adding WSO2 Developers mailing list] >>>>>> >>>>>> Hi Anurag, >>>>>> >>>>>> Please find my comments inline. >>>>>> >>>>>> First, which boosting model are we going to target-Ada boosting or >>>>>>> some other model, or various models? >>>>>> >>>>>> You can pick any method as you wish. >>>>>> >>>>>> >>>>>> Second, what method would you suggest I use to combine the results of >>>>>>> the models in stacking- is it going to be a single layer LR model? >>>>>> >>>>>> This has to be a user input (i.e. user should be able to pick any >>>>>> algorithm for the base-learners as well as for the meta-learner). >>>>>> >>>>>> Regards, >>>>>> Supun >>>>>> >>>>>> On Mon, Mar 7, 2016 at 5:15 PM, Anurag Kashyap <anurag1...@gmail.com> >>>>>> wrote: >>>>>> >>>>>>> Hi Supun, >>>>>>> I've begun reading the source rom link 3. I had a couple of >>>>>>> questions. First, which boosting model are we going to target-Ada >>>>>>> boosting >>>>>>> or some other model, or various models? Second, what method would you >>>>>>> suggest I use to combine the results of the models in stacking- is it >>>>>>> going >>>>>>> to be a single layer LR model? >>>>>>> >>>>>>> >>>>>>> >>>>>>> On Sun, Mar 6, 2016 at 6:25 PM, Supun Sethunga <sup...@wso2.com> >>>>>>> wrote: >>>>>>> >>>>>>>> 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 >>>>>>>> >>>>>>> >>>>>>> >>>>>>> >>>>>>> -- >>>>>>> Yours sincerely, >>>>>>> >>>>>>> *Anurag Kashyap* >>>>>>> *MSc.(Tech.)* Information Systems, >>>>>>> *BITS Pilani K K Birla Goa Campus* >>>>>>> >>>>>>> [image: Blog] <https://thelinuxkernel.wordpress.com> >>>>>>> >>>>>> >>>>>> >>>>>> >>>>>> -- >>>>>> *Supun Sethunga* >>>>>> Software Engineer >>>>>> WSO2, Inc. >>>>>> http://wso2.com/ >>>>>> lean | enterprise | middleware >>>>>> Mobile : +94 716546324 >>>>>> >>>>> >>>>> >>>>> >>>>> -- >>>>> Yours sincerely, >>>>> >>>>> *Anurag Kashyap* >>>>> *MSc.(Tech.)* Information Systems, >>>>> *BITS Pilani K K Birla Goa Campus* >>>>> >>>>> [image: Blog] <https://thelinuxkernel.wordpress.com> >>>>> >>>> >>>> >>>> >>>> -- >>>> *Supun Sethunga* >>>> Software Engineer >>>> WSO2, Inc. >>>> http://wso2.com/ >>>> lean | enterprise | middleware >>>> Mobile : +94 716546324 >>>> >>> >>> >>> >>> -- >>> Yours sincerely, >>> >>> *Anurag Kashyap* >>> *MSc.(Tech.)* Information Systems, >>> *BITS Pilani K K Birla Goa Campus* >>> >>> [image: Blog] <https://thelinuxkernel.wordpress.com> >>> >> >> >> >> -- >> *Supun Sethunga* >> Software Engineer >> WSO2, Inc. >> http://wso2.com/ >> lean | enterprise | middleware >> Mobile : +94 716546324 >> >> _______________________________________________ >> Dev mailing list >> Dev@wso2.org >> http://wso2.org/cgi-bin/mailman/listinfo/dev >> >> > > > -- > > Thanks & regards, > Nirmal > > Team Lead - WSO2 Machine Learner > Associate Technical Lead - Data Technologies Team, WSO2 Inc. > Mobile: +94715779733 > Blog: http://nirmalfdo.blogspot.com/ > > > -- *Supun Sethunga* Software Engineer WSO2, Inc. http://wso2.com/ lean | enterprise | middleware Mobile : +94 716546324
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