Hi Misgana,

Congratulations for getting accepted for the gsoc 2016! Hope you are ready
to get started with the project.

To get more familiarized with the code, I'm sharing the implementations of
the current algorithms [1]. For your ensemble method, you need to add three
more cases (for the three types of ensembles) for the method [2]. You may
try out adding a new algorithm to he existing flow, and see how it works.
Please feel free to raise any questions/issues you come across.

[1]
https://github.com/wso2/carbon-ml/tree/master/components/ml/org.wso2.carbon.ml.core/src/main/java/org/wso2/carbon/ml/core/spark/algorithms
[2]
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/SupervisedSparkModelBuilder.java#L101

Regards,
Supun

On Thu, Mar 24, 2016 at 9:31 PM, Misgana Negassi <
negas...@tf.uni-freiburg.de> wrote:

> Hi Supun,
>
> Thank you for your support and advice in this proposal process!
>
> In the case you are interested, I am attaching my report paper with
> contains my work with ensemble methods particularly Stacking.
>
> Best,
> Misgana
>
>
> On 24.03.2016 04:12, Supun Sethunga wrote:
>
> Looks good! Please go ahead and submit to GSoC.
>
> Thanks,
> Supun
>
> On Thu, Mar 24, 2016 at 4:02 AM, Misgana Negassi <
> negas...@tf.uni-freiburg.de> wrote:
>
>> Hi Supun,
>>
>> I have added the changes you recommended. Could you kindly give me a
>> feedback?
>>
>> Best,
>> Misgana
>>
>> On 23.03.2016 15:04, Supun Sethunga wrote:
>>
>> Hi Misgana,
>>
>> I went through your proposal. Overall it looks good. Here are a few
>> comments I would like to point out:
>>
>>    - Its better to have some sort of an architecture diagram, explaining
>>    your solution in a higher level.
>>    - In the timeline, better to break down the "Week 1­3 (May 23 ­ June
>>    20, 2016)" into three sub-levels, and allocate timeslots for each of the
>>    three methods (Stacking, Boosting and Bagging) separately. That would make
>>    it easy for you to work on those methods separately, as well as to track
>>    the progress.
>>    - In the timeline, can you double check the "week" numbers..? for eg;
>>    in [*Week 1­-3 (May 23 ­ June 20, 2016*], I guess it should be "*Week
>>    1-4*" (there are four weeks in the mentioned duration). Similarly,
>>    check the others too.
>>
>> Please share us the draft proposal once you fix those.
>>
>> Thanks,
>> Supun
>>
>> On Wed, Mar 23, 2016 at 7:17 PM, Misgana Negassi <
>> <negas...@tf.uni-freiburg.de>negas...@tf.uni-freiburg.de> wrote:
>>
>>> Hi Supun,
>>>
>>> I am attaching my proposal draft. I am very grateful for your comments.
>>>
>>> Thanks,
>>> Misgana
>>>
>>>
>>> On 23.03.2016 04:54, Supun Sethunga wrote:
>>>
>>> Hi Misgana,
>>>
>>> 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. (On technique per each of these methods)
>>>
>>> If you haven't tried out already, 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. You can also go through the source code of WSO2 ML
>>> ([4] and [5]), and get familiarized with the current implementations.
>>>
>>> Meantime, as Nirmal mentioned, can you please send us the draft of the
>>> proposal so that we can review it and give you a feedback?
>>>
>>> [1]  <http://wso2.com/products/machine-learner/>
>>> http://wso2.com/products/machine-learner/
>>> [2]  <https://docs.wso2.com/display/ML100/Introducing+Machine+Learner>
>>> https://docs.wso2.com/display/ML100/Introducing+Machine+Learner
>>> [3]
>>> <http://supunsetunga.blogspot.com/2015/09/building-your-first-predictive-model.html>
>>> http://supunsetunga.blogspot.com/2015/09/building-your-first-predictive-model.html
>>> [4]  <https://github.com/wso2/carbon-ml>
>>> https://github.com/wso2/carbon-ml
>>> [5]  <https://github.com/wso2/product-ml>
>>> https://github.com/wso2/product-ml
>>>
>>> Thanks,
>>> Supun
>>>
>>> On Wed, Mar 23, 2016 at 7:20 AM, Nirmal Fernando < <nir...@wso2.com>
>>> nir...@wso2.com> wrote:
>>>
>>>> Thanks, Misgana for your interest in a WSO2 ML GSoC project. Whilst I
>>>> let Supun give you some more information on the project, I encourage you to
>>>> create a draft proposal and send us for review.
>>>>
>>>> On Wed, Mar 23, 2016 at 2:58 AM, Misgana Negassi <
>>>> <negas...@tf.uni-freiburg.de>negas...@tf.uni-freiburg.de> wrote:
>>>>
>>>>> Hallo!
>>>>>
>>>>> I am Misgana, hailing from Freiburg, Germany and I am interested in
>>>>> working with you on the Ensemble methods . I have already implemented
>>>>> Stacking in python(code available in github/zemoel) and compared it to
>>>>> other ensemble methods such as Ensemble Selection on AUC performance
>>>>> measures. The comparison also included using above mentioned methods as
>>>>> part of an automated machine learning platform(Autosklearn).
>>>>>
>>>>> I am currently working on my proposal and would be grateful for your
>>>>> reply.
>>>>>
>>>>> Misgana
>>>>>
>>>>
>>>>
>>>>
>>>> --
>>>>
>>>> Thanks & regards,
>>>> Nirmal
>>>>
>>>> Team Lead - WSO2 Machine Learner
>>>> Associate Technical Lead - Data Technologies Team, WSO2 Inc.
>>>> Mobile: +94715779733
>>>> Blog: <http://nirmalfdo.blogspot.com/>http://nirmalfdo.blogspot.com/
>>>>
>>>>
>>>>
>>>
>>>
>>> --
>>> *Supun Sethunga*
>>> Software Engineer
>>> WSO2, Inc.
>>> <http://wso2.com/>http://wso2.com/
>>> lean | enterprise | middleware
>>> Mobile : +94 716546324 <%2B94%20716546324>
>>>
>>>
>>>
>>
>>
>> --
>> *Supun Sethunga*
>> Software Engineer
>> WSO2, Inc.
>> http://wso2.com/
>> lean | enterprise | middleware
>> Mobile : +94 716546324
>>
>>
>>
>
>
> --
> *Supun Sethunga*
> Software Engineer
> WSO2, Inc.
> <http://wso2.com/>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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