Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-06-29 Thread Supun Sethunga 
Hi,

I will check and let you know

Regards,
Supun

On Tue, Jun 28, 2016 at 5:33 AM, Misgana Negassi <
negas...@tf.uni-freiburg.de> wrote:

> Hi Supun,
>
> These are the links for the code I changed.
>
>
> https://github.com/zemoel/carbon-ml/blob/master/components/ml/org.wso2.carbon.ml.database/src/main/java/org/wso2/carbon/ml/database/DatabaseService.java#L422
>
> https://github.com/zemoel/carbon-ml/blob/master/components/ml/org.wso2.carbon.ml.database/src/main/java/org/wso2/carbon/ml/database/internal/MLDatabaseService.java#L2173
>
> https://github.com/zemoel/carbon-ml/blob/master/components/ml/org.wso2.carbon.ml.database/src/main/java/org/wso2/carbon/ml/database/internal/MLDatabaseService.java#L2506
>
> https://github.com/zemoel/carbon-ml/blob/master/components/ml/org.wso2.carbon.ml.commons/src/main/java/org/wso2/carbon/ml/commons/domain/Workflow.java#L267
>
> https://github.com/zemoel/carbon-ml/blob/master/components/ml/org.wso2.carbon.ml.commons/src/main/java/org/wso2/carbon/ml/commons/domain/Workflow.java#L280
>
> Best,
> Misgana
>
>
> On 27.06.2016 08:53, Supun Sethunga wrote:
>
> Hi Misgana,
>
> Can you commit all the changes to your fork of carbon-ml, and share us the
> link. So that I can check whats happening.
>
> Also, do I need to manually edit the machinelearner.xml file(s) to include
>> Stacking?
>
> Yes. No need to add hyper-parameters, since we can't predefine them.
>
> Thanks,
> Supun
>
> On Mon, Jun 27, 2016 at 4:33 AM, Misgana Negassi <
> negas...@tf.uni-freiburg.de> wrote:
>
>> Hello Supun,
>> sorry to bother you again with the same problem but I am not making any
>> progress right now :(
>> I can't get the sample script running.
>>
>> I tried two approaches:
>> A) Using the server provided and applying patches.
>> Problem: I can not apply my patch. I suspect the problem is that my patch
>> is of a newer version. The server's carbon ml is 1.1.1. and mine is 1.1.2.
>> Can I somewhere change the version number when I build my project?
>>
>> B) Building carbon and then product-ml and then unpacking
>> modules/distribution/target/wso2ml-2.0.0-SNAPSHOT.zip
>> I can start the server with the right components except for one exception:
>>
>> log4j:ERROR Could not instantiate appender named "CARBON_MEMORY".
>> log4j:ERROR Could not instantiate class
>> [org.wso2.carbon.logging.service.appender.CarbonMemoryAppender].
>> java.lang.ClassNotFoundException:
>> org.wso2.carbon.logging.service.appender.CarbonMemoryAppender cannot be
>> found by org.wso2.carbon.logging_4.4.3
>> at
>> org.eclipse.osgi.internal.loader.BundleLoader.findClassInternal(BundleLoader.java:501)
>>
>>
>> However, when I try to run my example script there seems to be nothing
>> happening on the server side. No exceptions but also the debugger does not
>> stop when I expect it would. It seems something is crashing but the
>> exceptions are swallowed. Is there a way to increase the debug output?
>>
>> Also, do I need to manually edit the machinelearner.xml file(s) to
>> include Stacking?
>>
>>
>> On 21.06.2016 05:41, Supun Sethunga wrote:
>>
>> Hi Misgana,
>>
>> I have two issues:
>> 1. Issue:
>>
>> Exception in thread "pool-17-thread-7" java.lang.IllegalArgumentException:
>>> No enum constant org.wso2.carbon.ml.commons.con
>>> stants.MLConstants.SUPERVISED_ALGORITHM.STACKING
>>> at java.lang.Enum.valueOf(Enum.java:238)
>>> at org.wso2.carbon.ml.commons.constants.MLConstants$SUPERVISED_
>>> ALGORITHM.valueOf(MLConstants.java:225)
>>> at org.wso2.carbon.ml.core.spark.algorithms.SupervisedSparkMode
>>> lBuilder.build(SupervisedSparkModelBuilder.java:158)
>>
>> Which approach did you try? putting the jar as a patch (patch)? or
>> build the carbon-ml and product ml respectively? If it was patching method,
>> did you build org.wso2.carbon.ml.commons as well?
>>
>> Caused by: org.wso2.carbon.ml.database.exceptions.DatabaseHandlerException:
>>> An error occurred while inserting hyper parameter  to the database: Value
>>> too long for column "VALUE VARCHAR(50)": "'rO0ABXNyABNqYXZhLnV0aWwuQXJy
>>> YXlMaXN0eIHSHZnHYZ0DAAFJAARzaXpleHACdwQCc3IAEWphdmEu
>>> dXRpbC5IYXNoTWFwBQfawcMWYNEDAAJGAApsb2F... (372)"; SQL statement:
>>> INSERT INTO ML_HYPER_PARAMETER(ANALYSIS_ID, ALGORITHM_NAME, NAME,
>>> VALUE, LAST_MODIFIED_TIME) VALUES(?,?,?,?, CURRENT_TIMESTAMP()) [90005-140]
>>> The Logic is: The hyperparameters of base-algorithms are serialized and
>>> passed in the product-ml hyperparamters script file.This is a serialized
>>> string of List of Maps, where each map contains hyperparameters of each
>>> base-algorithm and will be deserialized in buildStackingModel() in
>>> SupervisedSparkModelBuilder and fed to Stacking train().
>>> Current idea to solve it is:
>>>  1. Increase column capacity more than VALUE VARCHAR(50)
>>>  2. Change serialization logic
>>> What do you think?
>>
>>
>> I believe we don't need to pass a serialized a map and put the string in
>> DB. Can we store the hyperparamerets as follows, in the

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-06-27 Thread Supun Sethunga 
Hi Misgana,

Can you commit all the changes to your fork of carbon-ml, and share us the
link. So that I can check whats happening.

Also, do I need to manually edit the machinelearner.xml file(s) to include
> Stacking?

Yes. No need to add hyper-parameters, since we can't predefine them.

Thanks,
Supun

On Mon, Jun 27, 2016 at 4:33 AM, Misgana Negassi <
negas...@tf.uni-freiburg.de> wrote:

> Hello Supun,
> sorry to bother you again with the same problem but I am not making any
> progress right now :(
> I can't get the sample script running.
>
> I tried two approaches:
> A) Using the server provided and applying patches.
> Problem: I can not apply my patch. I suspect the problem is that my patch
> is of a newer version. The server's carbon ml is 1.1.1. and mine is 1.1.2.
> Can I somewhere change the version number when I build my project?
>
> B) Building carbon and then product-ml and then unpacking
> modules/distribution/target/wso2ml-2.0.0-SNAPSHOT.zip
> I can start the server with the right components except for one exception:
>
> log4j:ERROR Could not instantiate appender named "CARBON_MEMORY".
> log4j:ERROR Could not instantiate class
> [org.wso2.carbon.logging.service.appender.CarbonMemoryAppender].
> java.lang.ClassNotFoundException:
> org.wso2.carbon.logging.service.appender.CarbonMemoryAppender cannot be
> found by org.wso2.carbon.logging_4.4.3
> at
> org.eclipse.osgi.internal.loader.BundleLoader.findClassInternal(BundleLoader.java:501)
>
>
> However, when I try to run my example script there seems to be nothing
> happening on the server side. No exceptions but also the debugger does not
> stop when I expect it would. It seems something is crashing but the
> exceptions are swallowed. Is there a way to increase the debug output?
>
> Also, do I need to manually edit the machinelearner.xml file(s) to include
> Stacking?
>
>
> On 21.06.2016 05:41, Supun Sethunga wrote:
>
> Hi Misgana,
>
> I have two issues:
> 1. Issue:
>
> Exception in thread "pool-17-thread-7" java.lang.IllegalArgumentException:
>> No enum constant org.wso2.carbon.ml.commons.con
>> stants.MLConstants.SUPERVISED_ALGORITHM.STACKING
>> at java.lang.Enum.valueOf(Enum.java:238)
>> at org.wso2.carbon.ml.commons.constants.MLConstants$SUPERVISED_
>> ALGORITHM.valueOf(MLConstants.java:225)
>> at org.wso2.carbon.ml.core.spark.algorithms.SupervisedSparkMode
>> lBuilder.build(SupervisedSparkModelBuilder.java:158)
>
> Which approach did you try? putting the jar as a patch (patch)? or
> build the carbon-ml and product ml respectively? If it was patching method,
> did you build org.wso2.carbon.ml.commons as well?
>
> Caused by: org.wso2.carbon.ml.database.exceptions.DatabaseHandlerException:
>> An error occurred while inserting hyper parameter  to the database: Value
>> too long for column "VALUE VARCHAR(50)": "'rO0ABXNyABNqYXZhLnV0aWwuQXJy
>> YXlMaXN0eIHSHZnHYZ0DAAFJAARzaXpleHACdwQCc3IAEWphdmEu
>> dXRpbC5IYXNoTWFwBQfawcMWYNEDAAJGAApsb2F... (372)"; SQL statement:
>> INSERT INTO ML_HYPER_PARAMETER(ANALYSIS_ID, ALGORITHM_NAME, NAME, VALUE,
>> LAST_MODIFIED_TIME) VALUES(?,?,?,?, CURRENT_TIMESTAMP()) [90005-140]
>> The Logic is: The hyperparameters of base-algorithms are serialized and
>> passed in the product-ml hyperparamters script file.This is a serialized
>> string of List of Maps, where each map contains hyperparameters of each
>> base-algorithm and will be deserialized in buildStackingModel() in
>> SupervisedSparkModelBuilder and fed to Stacking train().
>> Current idea to solve it is:
>>  1. Increase column capacity more than VALUE VARCHAR(50)
>>  2. Change serialization logic
>> What do you think?
>
>
> I believe we don't need to pass a serialized a map and put the string in
> DB. Can we store the hyperparamerets as follows, in the ML_HYPER_PARAMETER
> table?
>
> *ANALYSIS_ID* *ALGORITHM_NAME* *NAME* *VALUE* *LAST_MODIFIED_TIME*
> 123 Meta_Algorithm_1 Learning Rate 0.001 
> 123 Meta_Algorithm_1 Num_Trees 10 
> 123 Meta_Algorithm_1 Max_Depth 0.001 
> 123 Meta_Algorithm_1 Seed 4567 
> 123 Meta_Algorithm_2 Learning Rate 0.001 
> 123 Meta_Algorithm_2 Iterations 100 
> 123 Meta_Algorithm_2 Seed 789 
> … … … … …
> 123 Base_Algorithm Learning Rate 0.001 
> 123 Base_Algorithm Iterations 100 
> 123 Base_Algorithm Seed 6325 
>
> Do you see any complications/issues in doing so?
>
>
>
> Thanks,
> Supun
>
> On Mon, Jun 20, 2016 at 6:58 PM, Misgana Negassi <
> negas...@tf.uni-freiburg.de> wrote:
>
>> Hi Supun,
>>
>> I have two issues:
>> 1. Issue:
>>
>> Exception in thread "pool-17-thread-7"
>> java.lang.IllegalArgumentException: No enum constant
>> org.wso2.carbon.ml.commons.constants.MLConstants.SUPERVISED_ALGORITHM.STACKING
>> at java.lang.Enum.valueOf(Enum.java:238)
>> at
>> org.wso2.carbon.ml.commons.constants.MLConstants$SUPERVISED_ALGORITHM.valueOf(MLConstants.java:225)
>> at
>> org.wso2.carbon.ml.core.spark.algorithms.SupervisedSparkModelBuilder.build(SupervisedSparkModelBuilder.java:158)
>>
>>
>> It doesn't

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-06-20 Thread Supun Sethunga 
Hi Misgana,

I have two issues:
1. Issue:

Exception in thread "pool-17-thread-7" java.lang.IllegalArgumentException:
> No enum constant org.wso2.carbon.ml.commons.con
> stants.MLConstants.SUPERVISED_ALGORITHM.STACKING
> at java.lang.Enum.valueOf(Enum.java:238)
> at org.wso2.carbon.ml.commons.constants.MLConstants$SUPERVISED_
> ALGORITHM.valueOf(MLConstants.java:225)
> at org.wso2.carbon.ml.core.spark.algorithms.SupervisedSparkMode
> lBuilder.build(SupervisedSparkModelBuilder.java:158)

Which approach did you try? putting the jar as a patch (patch)? or
build the carbon-ml and product ml respectively? If it was patching method,
did you build org.wso2.carbon.ml.commons as well?

Caused by: org.wso2.carbon.ml.database.exceptions.DatabaseHandlerException:
> An error occurred while inserting hyper parameter  to the database: Value
> too long for column "VALUE VARCHAR(50)": "'rO0ABXNyABNqYXZhLnV0aWwuQXJy
> YXlMaXN0eIHSHZnHYZ0DAAFJAARzaXpleHACdwQCc3IAEWphdmEu
> dXRpbC5IYXNoTWFwBQfawcMWYNEDAAJGAApsb2F... (372)"; SQL statement:
> INSERT INTO ML_HYPER_PARAMETER(ANALYSIS_ID, ALGORITHM_NAME, NAME, VALUE,
> LAST_MODIFIED_TIME) VALUES(?,?,?,?, CURRENT_TIMESTAMP()) [90005-140]
> The Logic is: The hyperparameters of base-algorithms are serialized and
> passed in the product-ml hyperparamters script file.This is a serialized
> string of List of Maps, where each map contains hyperparameters of each
> base-algorithm and will be deserialized in buildStackingModel() in
> SupervisedSparkModelBuilder and fed to Stacking train().
> Current idea to solve it is:
>  1. Increase column capacity more than VALUE VARCHAR(50)
>  2. Change serialization logic
> What do you think?


I believe we don't need to pass a serialized a map and put the string in
DB. Can we store the hyperparamerets as follows, in the ML_HYPER_PARAMETER
table?

*ANALYSIS_ID* *ALGORITHM_NAME* *NAME* *VALUE* *LAST_MODIFIED_TIME*
123 Meta_Algorithm_1 Learning Rate 0.001 
123 Meta_Algorithm_1 Num_Trees 10 
123 Meta_Algorithm_1 Max_Depth 0.001 
123 Meta_Algorithm_1 Seed 4567 
123 Meta_Algorithm_2 Learning Rate 0.001 
123 Meta_Algorithm_2 Iterations 100 
123 Meta_Algorithm_2 Seed 789 
… … … … …
123 Base_Algorithm Learning Rate 0.001 
123 Base_Algorithm Iterations 100 
123 Base_Algorithm Seed 6325 

Do you see any complications/issues in doing so?



Thanks,
Supun

On Mon, Jun 20, 2016 at 6:58 PM, Misgana Negassi <
negas...@tf.uni-freiburg.de> wrote:

> Hi Supun,
>
> I have two issues:
> 1. Issue:
>
> Exception in thread "pool-17-thread-7" java.lang.IllegalArgumentException:
> No enum constant
> org.wso2.carbon.ml.commons.constants.MLConstants.SUPERVISED_ALGORITHM.STACKING
> at java.lang.Enum.valueOf(Enum.java:238)
> at
> org.wso2.carbon.ml.commons.constants.MLConstants$SUPERVISED_ALGORITHM.valueOf(MLConstants.java:225)
> at
> org.wso2.carbon.ml.core.spark.algorithms.SupervisedSparkModelBuilder.build(SupervisedSparkModelBuilder.java:158)
>
>
> It doesn't recognize STACKING although I have built carbonml as you have
> described.
>
> 2. Issue
>
>
> Caused by:
> org.wso2.carbon.ml.database.exceptions.DatabaseHandlerException: An error
> occurred while inserting hyper parameter  to the database: Value too long
> for column "VALUE VARCHAR(50)":
> "'rO0ABXNyABNqYXZhLnV0aWwuQXJyYXlMaXN0eIHSHZnHYZ0DAAFJAARzaXpleHACdwQCc3IAEWphdmEudXRpbC5IYXNoTWFwBQfawcMWYNEDAAJGAApsb2F...
> (372)"; SQL statement:
> INSERT INTO ML_HYPER_PARAMETER(ANALYSIS_ID, ALGORITHM_NAME, NAME, VALUE,
> LAST_MODIFIED_TIME) VALUES(?,?,?,?, CURRENT_TIMESTAMP()) [90005-140]
>
> The Logic is: The hyperparameters of base-algorithms are serialized and
> passed in the product-ml hyperparamters script file.This is a serialized
> string of List of Maps, where each map contains hyperparameters of each
> base-algorithm and will be deserialized in buildStackingModel() in
> SupervisedSparkModelBuilder and fed to Stacking train().
>
> Current idea to solve it is:
>  1. Increase column capacity more than VALUE VARCHAR(50)
>  2. Change serialization logic
>
> What do you think?
>
> Regards,
> Misgana
>
>
>
>
> Can you specify why what was the error? Is there any error/stack trace?
>>
>
>


-- 
*Supun Sethunga*
Senior Software Engineer
WSO2, Inc.
http://wso2.com/
lean | enterprise | middleware
Mobile : +94 716546324
Blog: http://supunsetunga.blogspot.com
___
Dev mailing list
Dev@wso2.org
http://wso2.org/cgi-bin/mailman/listinfo/dev

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-06-13 Thread Supun Sethunga 
Hi Misgana,

That's a pretty good job!

I have integrated a working version of Stacking into the
> SupervisedSparkModelBuilder. My implementation is naive (potential
> unnecessary conversions) but I would keep it to test against a more
> efficient implementation. Please find the details below.

I also wanted to adapt the graphical user interface but I have no idea
> where to start. Can you give me a hint?

Let's not worry about the performance/efficiency for the moment. We can do
it as an improvement later on, if time permits.
Anyway, were you able to run the standalone one (the one you wrote as a
java client), for a Test dataset?

If it works without any issues, then before we move on to the UI
implementation, shall we test the integration using the REST API? (even the
UI call this rest API. So we should be able to do the same operation using
this REST API, without the UI. If that works fine too, then we will move to
the UI part?)

[1] is a built-in sample, which builds a Random Forest Classification model
from end to end, using the REST APIs. Can you use the same APIs in the same
order, and try to build a Stacking Model and see if it works fine? Please
note, when you are invoking the REST API, Need to make sure you pass the
correct values, especially for:

   - setting model configs - Need to pass, not only the Algorithm Name
   ("Stacking"), but also the Base/Meta algorithm names as well.
   - setting hyper params - Need to add Hyper-parameters for all the base
   and meta algorithms. Hence, the Algorithm name should be "Meta_algorithm_x"
   or something similar (but *not* "Stacking" *nor* the actual algorithm
   name used for base algorithm x, such as "Random Forest" )

Also, to achieve above, you might have to modify the DB schema [2], and in
the Table "*Hyper_Parameters*" make the *algorithm_name* a primary key as
well. Otherwise, there can be duplicates.
If you have any doubts please feel free to ask.

Also, Since the Mid-evaluation is near, Can you please arrange a session
(Hangouts would be fine) to do small demo on the current work you did, and
run a small sample with stacking (with the standalone java client you
implemented) to show how it works? It would be great if you can set it in
an IST (GMT + 0530 ) friendly time slot.

[1]
https://github.com/wso2/product-ml/blob/master/modules/samples/tuned/random-forest-classification/model-generation.sh
[2]
https://docs.wso2.com/display/ML110/Architecture#Architecture-Databasedesign

Thanks,
Supun

On Mon, Jun 13, 2016 at 10:02 PM, Misgana Negassi <
negas...@tf.uni-freiburg.de> wrote:

> Hi Supun,
>
> I have integrated a working version of Stacking into the
> SupervisedSparkModelBuilder. My implementation is naive (potential
> unnecessary conversions) but I would keep it to test against a more
> efficient implementation. Please find the details below.
>
> I also wanted to adapt the graphical user interface but I have no idea
> where to start. Can you give me a hint?
>
> Best,
> Misgana
>
> DETAILS:
>
> UI LOGIC(My approach):
>  I expect a list of base-algorithms together with their parameters from
> the UI. That means, if the user selects Stacking, he will presented with UI
> to select the number of base-algorithms to train. After choosing a
> base-algorithm, he will be prompted to select parameters for each algorithm
> and is then redirected to selecting a meta-algorithm and also set its
> parameters.  This will be serialized and fed to carbon-ml.Finally,train.
>
> INTEGRATION:
>
> Here is the current work status:
>
>
> 1. buildStackingModel method for SupervisedSparkModelBuilder [1]:
>
> STATUS :  Method implementation completed.
>
> LOGIC: We expect, a list of base-Algorithms together with their
> parameters(serialized). Deserialized, this will be fed to Stacking Class to
> train. To this end, I have  added in MLCONSTANTS class, the hyperparameters
> needed.
> Next Step, is to invoke Stacking test() method and
> build ModelSummary.
>
> 2. Stacking Class: [2]
>
> STATUS:  Naive implementation with working code completed.
>
> LOGIC: This class implements ClassificationModel.
>
>  For train() method, the idea is to implement the four main
> Steps in Stacking Logic.
> Step1. Train list of basemodels(level0) on cross-validated
> data. For this, I implemented a BaseModelBuilder Class which is similiar in
> logic to SupervisedSparkModelBuilder except, it returns a model of MLModel
> datatype.
> Step2. get predictions of each List (we use here
> predict() method of Predictor class) and combine predictions to get level1
> dataset
> Step3. train Meta-Algorithm on level1dataset
> Step4. train base-algorithms on whole dataset and store
> list base models.
>
>For test() method, we create a level1_test_dataset by combining
> predictions of basemodels (trained on the whole dataset) on the
> level0_test_dataset. Finally, we get final

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-06-12 Thread Supun Sethunga 
Hi Misgana,

How is the work going so far? Can you give a brief update on the current
status, and what is left to be done?

Thanks,
Supun

On Wed, Jun 8, 2016 at 5:54 PM, Misgana Negassi  wrote:

> Hi Supun,
>
> Thank you for your suggestions. I would like to abstract from the concrete
> the level0 models and concrete level1 model and needed a suitable interface
> for that. MLModel seemed a good choice also in perspective of later
> integration of  stacking.
>
> From my point of view the native spark models are not suitable because
> they don't share a suitable interface like MLModel. My approach is to use
> those native spark models and convert them to carbonml type models using
> eg. MLRandomForest.setModel() for RandomForestModel.
>
> Also now I found a way to use the Predictor without a configuration
> context by passing an empty encoding.
>
> I will put extra effort to meet the deadline and create code which is
> scalable to later change/integration. I apologize for any miscommunication
> that may arise from my side.
>
> Best regards,
> Misgana
>
> On 08.06.2016 05:35, Supun Sethunga wrote:
>
> Hi,
>
> Also just a gentle reminder.., we have just under two weeks for the
> mid-term evaluation. We need to have some end to end working scenario of
> stacking by then. So lets put some extra effort and try to complete one
> scenario.
>
> Thanks,
> Supun
>
> On Tue, Jun 7, 2016 at 10:48 PM, Supun Sethunga  wrote:
>
>> Hi,
>>
>> I have restructured my code, see [1][2]. It is a naive implementation if
>>> my logic works.
>>
>> Why there are two files/implementations? which is the correct one? Say,
>> if I want to try out your implementation, which one should I run?
>>
>> When creating an instance of Stacking class, I need to pass an argument
>>> of type MLModelConfigurationContext. and getcontext() method doesn't work
>>> as I am in a static main method.
>>> Question: 1. What is the best way to get context argument?
>>> 2.  Is the design of Stacking class fine?
>>
>>
>> Why would you need to use MLModelConfigurationContext. and getcontext()
>> methods? Those are utility methods used at the ML server runtime to
>> temporary store configurations. Let's not worry about those, as they are
>> part of the integration phase. First, try to implement the stacking with
>> native spark-mllib libraries, and re-use methods/components in ML server 
>> *ONLY
>> IF * they are necessary or they are re-usable (i.e: if some method is
>> already available, which you need).
>>
>> Regards,
>> Supun
>>
>> On Tue, Jun 7, 2016 at 8:31 PM, Misgana Negassi <
>> negas...@tf.uni-freiburg.de> wrote:
>>
>>>
>>> Hi Supun,
>>>
>>> My dependencies problems are solved, thanks!
>>>
>>> I have restructured my code, see [1][2]. It is a naive implementation if
>>> my logic works.
>>>
>>>
>>> When creating an instance of Stacking class, I need to pass an argument
>>> of type MLModelConfigurationContext. and getcontext() method doesn't work
>>> as I am in a static main method.
>>> Question: 1. What is the best way to get context argument?
>>> 2.  Is the design of Stacking class fine?
>>>
>>> I appreciate your feedback!
>>> Misgana
>>>
>>>
>>>
>>>
>>>
>>> [1]
>>> https://github.com/zemoel/ensemble-methods/blob/master/src/main/java/Stacking.java
>>> [2]
>>> https://github.com/zemoel/ensemble-methods/blob/master/src/main/java/ReadCSV.java#L188
>>>
>>>
>>> On 04.06.2016 06:18, Supun Sethunga wrote:
>>>
>>> Hi,
>>>
>>> Can you check whether you have defined the relevant repositories in the
>>> pom.xml? If haven't, please do so as in [1].
>>>
>>> If that didn't work out, can you try checking out the source code of
>>> [2], and build it locally, and then build your code?
>>>
>>> [1] https://github.com/wso2/carbon-ml/blob/master/pom.xml#L59
>>> [2]
>>> https://github.com/wso2/carbon-metrics/tree/v1.1.0/components/org.wso2.carbon.metrics.manager
>>>
>>> Regards,
>>>
>>> On Fri, Jun 3, 2016 at 7:06 PM, Misgana Negassi <
>>> negas...@tf.uni-freiburg.de> wrote:
>>>
 Hi Supun,

 This  is [1] the predict() method invoked.

 I added the dependencies and run mvn clean install and am trying to
 debug this error now:



 *Failed to execute goal on project ensemble-methods: Could not resolve
 dependencies for project
 org.wso2.carbon.ml:ensemble-methods:jar:1.0-SNAPSHOT: The following
 artifacts could not be resolved:
 org.wso2.carbon.metrics:org.wso2.carbon.metrics.manager:jar:1.1.0 *Best




 [1]
 https://github.com/wso2/carbon-ml/blob/master/components/ml/org.wso2.carbon.ml.core/src/main/java/org/wso2/carbon/ml/core/impl/Predictor.java#L80

 On 03.06.2016 14:11, Supun Sethunga wrote:

 Hi,

 Can you specify which predict() method, to be precise?

 Anyway, looking at the error trace, this seems to be a version mismatch

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-06-07 Thread Supun Sethunga 
Hi,

Also just a gentle reminder.., we have just under two weeks for the
mid-term evaluation. We need to have some end to end working scenario of
stacking by then. So lets put some extra effort and try to complete one
scenario.

Thanks,
Supun

On Tue, Jun 7, 2016 at 10:48 PM, Supun Sethunga  wrote:

> Hi,
>
> I have restructured my code, see [1][2]. It is a naive implementation if
>> my logic works.
>
> Why there are two files/implementations? which is the correct one? Say, if
> I want to try out your implementation, which one should I run?
>
> When creating an instance of Stacking class, I need to pass an argument of
>> type MLModelConfigurationContext. and getcontext() method doesn't work as I
>> am in a static main method.
>> Question: 1. What is the best way to get context argument?
>> 2.  Is the design of Stacking class fine?
>
>
> Why would you need to use MLModelConfigurationContext. and getcontext()
> methods? Those are utility methods used at the ML server runtime to
> temporary store configurations. Let's not worry about those, as they are
> part of the integration phase. First, try to implement the stacking with
> native spark-mllib libraries, and re-use methods/components in ML server *ONLY
> IF * they are necessary or they are re-usable (i.e: if some method is
> already available, which you need).
>
> Regards,
> Supun
>
> On Tue, Jun 7, 2016 at 8:31 PM, Misgana Negassi <
> negas...@tf.uni-freiburg.de> wrote:
>
>>
>> Hi Supun,
>>
>> My dependencies problems are solved, thanks!
>>
>> I have restructured my code, see [1][2]. It is a naive implementation if
>> my logic works.
>>
>>
>> When creating an instance of Stacking class, I need to pass an argument
>> of type MLModelConfigurationContext. and getcontext() method doesn't work
>> as I am in a static main method.
>> Question: 1. What is the best way to get context argument?
>> 2.  Is the design of Stacking class fine?
>>
>> I appreciate your feedback!
>> Misgana
>>
>>
>>
>>
>>
>> [1]
>> https://github.com/zemoel/ensemble-methods/blob/master/src/main/java/Stacking.java
>> [2]
>> https://github.com/zemoel/ensemble-methods/blob/master/src/main/java/ReadCSV.java#L188
>>
>>
>> On 04.06.2016 06:18, Supun Sethunga wrote:
>>
>> Hi,
>>
>> Can you check whether you have defined the relevant repositories in the
>> pom.xml? If haven't, please do so as in [1].
>>
>> If that didn't work out, can you try checking out the source code of [2],
>> and build it locally, and then build your code?
>>
>> [1] https://github.com/wso2/carbon-ml/blob/master/pom.xml#L59
>> [2]
>> https://github.com/wso2/carbon-metrics/tree/v1.1.0/components/org.wso2.carbon.metrics.manager
>>
>> Regards,
>>
>> On Fri, Jun 3, 2016 at 7:06 PM, Misgana Negassi <
>> negas...@tf.uni-freiburg.de> wrote:
>>
>>> Hi Supun,
>>>
>>> This  is [1] the predict() method invoked.
>>>
>>> I added the dependencies and run mvn clean install and am trying to
>>> debug this error now:
>>>
>>>
>>>
>>> *Failed to execute goal on project ensemble-methods: Could not resolve
>>> dependencies for project
>>> org.wso2.carbon.ml:ensemble-methods:jar:1.0-SNAPSHOT: The following
>>> artifacts could not be resolved:
>>> org.wso2.carbon.metrics:org.wso2.carbon.metrics.manager:jar:1.1.0 *Best
>>>
>>>
>>>
>>>
>>> [1]
>>> https://github.com/wso2/carbon-ml/blob/master/components/ml/org.wso2.carbon.ml.core/src/main/java/org/wso2/carbon/ml/core/impl/Predictor.java#L80
>>>
>>> On 03.06.2016 14:11, Supun Sethunga wrote:
>>>
>>> Hi,
>>>
>>> Can you specify which predict() method, to be precise?
>>>
>>> Anyway, looking at the error trace, this seems to be a version mismatch
>>> for the dependency "org.wso2.carbon.metrics ". Can you try adding v1.1.0
>>> ?
>>> i.e:  org.wso2.carbon.metrics
>>> org.wso2.carbon.metrics.manager 
>>> 1.1.0
>>> 
>>> Regards,
>>>
>>> On Fri, Jun 3, 2016 at 5:21 PM, Misgana Negassi <
>>> negas...@tf.uni-freiburg.de> wrote:
>>>
 Hi Supun,
 I get this error when calling predict() method.

 Exception in thread "main" java.lang.NoClassDefFoundError:
 org/wso2/carbon/metrics/manager/Level
 at
 org.wso2.carbon.ml.core.impl.Predictor.getTimer(Predictor.java:301)
 at org.wso2.carbon.ml.core.impl.Predictor.predict(Predictor.java:83)
 at testing.main(testing.java:27)
 at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
 at
 sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
 at
 sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
 at java.lang.reflect.Method.invoke(Method.java:497)
 at
 com.intellij.rt.execution.application.AppMain.main(AppMain.java:144)
 Caused by: java.lang.ClassNotFoundException:
 org.wso2.carbon.metrics.manager.Level
 at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
 at

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-06-07 Thread Supun Sethunga 
Hi,

I have restructured my code, see [1][2]. It is a naive implementation if my
> logic works.

Why there are two files/implementations? which is the correct one? Say, if
I want to try out your implementation, which one should I run?

When creating an instance of Stacking class, I need to pass an argument of
> type MLModelConfigurationContext. and getcontext() method doesn't work as I
> am in a static main method.
> Question: 1. What is the best way to get context argument?
> 2.  Is the design of Stacking class fine?


Why would you need to use MLModelConfigurationContext. and getcontext()
methods? Those are utility methods used at the ML server runtime to
temporary store configurations. Let's not worry about those, as they are
part of the integration phase. First, try to implement the stacking with
native spark-mllib libraries, and re-use methods/components in ML server *ONLY
IF * they are necessary or they are re-usable (i.e: if some method is
already available, which you need).

Regards,
Supun

On Tue, Jun 7, 2016 at 8:31 PM, Misgana Negassi  wrote:

>
> Hi Supun,
>
> My dependencies problems are solved, thanks!
>
> I have restructured my code, see [1][2]. It is a naive implementation if
> my logic works.
>
>
> When creating an instance of Stacking class, I need to pass an argument of
> type MLModelConfigurationContext. and getcontext() method doesn't work as I
> am in a static main method.
> Question: 1. What is the best way to get context argument?
> 2.  Is the design of Stacking class fine?
>
> I appreciate your feedback!
> Misgana
>
>
>
>
>
> [1]
> https://github.com/zemoel/ensemble-methods/blob/master/src/main/java/Stacking.java
> [2]
> https://github.com/zemoel/ensemble-methods/blob/master/src/main/java/ReadCSV.java#L188
>
>
> On 04.06.2016 06:18, Supun Sethunga wrote:
>
> Hi,
>
> Can you check whether you have defined the relevant repositories in the
> pom.xml? If haven't, please do so as in [1].
>
> If that didn't work out, can you try checking out the source code of [2],
> and build it locally, and then build your code?
>
> [1] https://github.com/wso2/carbon-ml/blob/master/pom.xml#L59
> [2]
> https://github.com/wso2/carbon-metrics/tree/v1.1.0/components/org.wso2.carbon.metrics.manager
>
> Regards,
>
> On Fri, Jun 3, 2016 at 7:06 PM, Misgana Negassi <
> negas...@tf.uni-freiburg.de> wrote:
>
>> Hi Supun,
>>
>> This  is [1] the predict() method invoked.
>>
>> I added the dependencies and run mvn clean install and am trying to debug
>> this error now:
>>
>>
>>
>> *Failed to execute goal on project ensemble-methods: Could not resolve
>> dependencies for project
>> org.wso2.carbon.ml:ensemble-methods:jar:1.0-SNAPSHOT: The following
>> artifacts could not be resolved:
>> org.wso2.carbon.metrics:org.wso2.carbon.metrics.manager:jar:1.1.0 *Best
>>
>>
>>
>>
>> [1]
>> https://github.com/wso2/carbon-ml/blob/master/components/ml/org.wso2.carbon.ml.core/src/main/java/org/wso2/carbon/ml/core/impl/Predictor.java#L80
>>
>> On 03.06.2016 14:11, Supun Sethunga wrote:
>>
>> Hi,
>>
>> Can you specify which predict() method, to be precise?
>>
>> Anyway, looking at the error trace, this seems to be a version mismatch
>> for the dependency "org.wso2.carbon.metrics ". Can you try adding v1.1.0?
>> i.e:  org.wso2.carbon.metrics
>> org.wso2.carbon.metrics.manager 
>> 1.1.0
>> 
>> Regards,
>>
>> On Fri, Jun 3, 2016 at 5:21 PM, Misgana Negassi <
>> negas...@tf.uni-freiburg.de> wrote:
>>
>>> Hi Supun,
>>> I get this error when calling predict() method.
>>>
>>> Exception in thread "main" java.lang.NoClassDefFoundError:
>>> org/wso2/carbon/metrics/manager/Level
>>> at
>>> org.wso2.carbon.ml.core.impl.Predictor.getTimer(Predictor.java:301)
>>> at org.wso2.carbon.ml.core.impl.Predictor.predict(Predictor.java:83)
>>> at testing.main(testing.java:27)
>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>> at
>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
>>> at
>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>>> at java.lang.reflect.Method.invoke(Method.java:497)
>>> at
>>> com.intellij.rt.execution.application.AppMain.main(AppMain.java:144)
>>> Caused by: java.lang.ClassNotFoundException:
>>> org.wso2.carbon.metrics.manager.Level
>>> at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
>>> at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
>>> at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:331)
>>> at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
>>>
>>>
>>> I added the module dependency "org.wso2.carbon.metrics " but still the
>>> error persists. Appreciate your help!
>>>
>>> Best,
>>> Misgana
>>>
>>>
>>> On 02.06.2016 10:49, Supun Sethunga wrote:
>>>
>>> Hi,
>>>
>>> A sample on how to invoke the predict() method can be found in the above
>>> links ([1], [2], [3]

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-05-16 Thread Supun Sethunga 
Can you try doing a "mvn clean"?

Do you get any compilation failures?

Regards,
Supun

On Thu, May 12, 2016 at 7:48 PM, Misgana Negassi <
negas...@tf.uni-freiburg.de> wrote:

> Hi Supun,
>
> Thank you for the supportive hangout session.
>
> I had one question I forgot to ask.
>
> When I was importing the carbon-ml as maven project to Eclipse I had this
> error message.
> *Multiple annotations found at this line:*
> *- Plugin execution not covered by lifecycle configuration:
> org.apache.felix:maven-scr-plugin:1.7.2:scr (execution:
> generate-scr-scrdescriptor, phase: process-*
> * classes)*
>
>
> *- maven-remote-resources-plugin (goal "process") is ignored by m2e. *How
> did you solve this problem if you have enountered it?
>
> Best,
> Misgana
>
>
> On 09.05.2016 06:12, Supun Sethunga wrote:
>
> Hi Misgana,
>
> I committed the code for reading a csv file. My next task will be sampling
>> and starting to implement an ensemble method(Stacking).
>
> I went through the code. Would like to suggest a small thing. Most of the
> Spark algorithms need JavaRDDs as the input for datasets. Hence reading
> your file as a JavaRDD is the better approach than reading it
> as a list of labelled points. Please refer [1] and [2] for an example.
>
> -  How to decide which models to use for an ensemble and which parameters?
>
> Type of Model/Algorithm has to be a user input. The parameters will
> depend on the algorithm user picks.
>
> - Should the ensemble methods be implemented as a wrapper around the
>> base-models?
>
> Yes.  You can use the existing algorithms in WSO2 Machine Learner, as the
> base-models. (I have shared that in my previous mail)
>
>
>> - Which library to use for matrix operations? Is Apache
>> commons.math.Linearalgebra ok?
>
> Yes  Apache commons.math.* would be fine. Infact you can use any library
> with open-source licence.
>
>
> What do you think about a hangout session to clarify stuff and get to know
>> each other.:)
>
> Of course! Please arrange some time slot (Hope it will be IST time zone:
> GMT+5.30 friendly :) ) and send me a calendar invite.
>
>
> [1]
> https://github.com/wso2/carbon-ml/blob/master/components/ml/org.wso2.carbon.ml.core/src/main/java/org/wso2/carbon/ml/core/utils/MLUtils.java#L58
> [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#L87
>
> Regards,
> Supun
>
> On Sat, May 7, 2016 at 8:46 PM, Misgana Negassi <
> negas...@tf.uni-freiburg.de> wrote:
>
>>
>> Hi Supun,
>> I committed the code for reading a csv file. My next task will be
>> sampling and starting to implement an ensemble method(Stacking).
>> I have some questions about:
>> -  How to decide which models to use for an ensemble and which
>> parameters?
>> - Should the ensemble methods be implemented as a wrapper around the
>> base-models?
>> - Which library to use for matrix operations? Is Apache
>> commons.math.Linearalgebra ok?
>>
>> What do you think about a hangout session to clarify stuff and get to
>> know each other.:)
>>
>> Have a nice weekend!
>> Misgana
>>
>>
>> On 05.05.2016 19:59, Misgana Negassi wrote:
>>
>> Hi Supun,
>> Thank you for the detailed explanation.
>>
>> I switched to intelliJ IDEA as an IDE with Ubuntu 14.04. The import
>> errors are resolved after the project was imported as maven project. This
>> took a while because of persistent pom.xml errors -- I am still in the
>> process of reading  about maven, Spark, REST and the carbon-Architecture.
>> I have created an independent maven-project[1] for the implementation of
>> the ensemble-methods. Currently I am writing code for reading a CSV file
>> using the Apache library and converting it into Java RDD. I will commit
>> once I am done with it.
>>
>>
>>
>> Regards,
>> Misgana
>>
>>
>> [1]https://github.com/zemoel/ensemble-methods
>>
>>
>> On 04.05.2016 06:33, Supun Sethunga wrote:
>>
>> Hi Misgana,
>>
>> Seems you have misunderstood the "carbon" architecture. Let me explain
>> it.  *carbon-ml* repo contains the source code of the osgi bundles (i.e:
>> jar libraries) which contain actual implementation/logic (such as, the
>> implementation of importing datasets, creating projects, building models,
>> and etc). Hence, these are similar to any other third-party library, which
>> you have to invoke using their APIs. (They don't have main classes, they
>> have APIs). This repo also contains a REST API, which exposes the
>> above-mentioned APIs as a RESTful service. It also includes the source code
>> for the UI, which invokes those REST APIs, behalf of the user. Please refer
>> [1] to get the overall idea.
>> Whereas, *product-ml* repo contains the source code, which collects the
>> necessary libraries (such as the libraries of carbon-ml, REST API, UI) and
>> bundles it all together, to create the final binary distribution.
>>
>> *carbon-ml* already contains the implementations of number of algorithms
>> [2].

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-05-08 Thread Supun Sethunga 
Hi Misgana,

I committed the code for reading a csv file. My next task will be sampling
> and starting to implement an ensemble method(Stacking).

I went through the code. Would like to suggest a small thing. Most of the
Spark algorithms need JavaRDDs as the input for datasets. Hence reading
your file as a JavaRDD is the better approach than reading it
as a list of labelled points. Please refer [1] and [2] for an example.

-  How to decide which models to use for an ensemble and which parameters?

Type of Model/Algorithm has to be a user input. The parameters will
depend on the algorithm user picks.

- Should the ensemble methods be implemented as a wrapper around the
> base-models?

Yes.  You can use the existing algorithms in WSO2 Machine Learner, as the
base-models. (I have shared that in my previous mail)


> - Which library to use for matrix operations? Is Apache
> commons.math.Linearalgebra ok?

Yes  Apache commons.math.* would be fine. Infact you can use any library
with open-source licence.


What do you think about a hangout session to clarify stuff and get to know
> each other.:)

Of course! Please arrange some time slot (Hope it will be IST time zone:
GMT+5.30 friendly :) ) and send me a calendar invite.


[1]
https://github.com/wso2/carbon-ml/blob/master/components/ml/org.wso2.carbon.ml.core/src/main/java/org/wso2/carbon/ml/core/utils/MLUtils.java#L58
[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#L87

Regards,
Supun

On Sat, May 7, 2016 at 8:46 PM, Misgana Negassi  wrote:

>
> Hi Supun,
> I committed the code for reading a csv file. My next task will be sampling
> and starting to implement an ensemble method(Stacking).
> I have some questions about:
> -  How to decide which models to use for an ensemble and which parameters?
> - Should the ensemble methods be implemented as a wrapper around the
> base-models?
> - Which library to use for matrix operations? Is Apache
> commons.math.Linearalgebra ok?
>
> What do you think about a hangout session to clarify stuff and get to know
> each other.:)
>
> Have a nice weekend!
> Misgana
>
>
> On 05.05.2016 19:59, Misgana Negassi wrote:
>
> Hi Supun,
> Thank you for the detailed explanation.
>
> I switched to intelliJ IDEA as an IDE with Ubuntu 14.04. The import errors
> are resolved after the project was imported as maven project. This took a
> while because of persistent pom.xml errors -- I am still in the process of
> reading  about maven, Spark, REST and the carbon-Architecture.
> I have created an independent maven-project[1] for the implementation of
> the ensemble-methods. Currently I am writing code for reading a CSV file
> using the Apache library and converting it into Java RDD. I will commit
> once I am done with it.
>
>
>
> Regards,
> Misgana
>
>
> [1]https://github.com/zemoel/ensemble-methods
>
>
> On 04.05.2016 06:33, Supun Sethunga wrote:
>
> Hi Misgana,
>
> Seems you have misunderstood the "carbon" architecture. Let me explain it.
>  *carbon-ml* repo contains the source code of the osgi bundles (i.e: jar
> libraries) which contain actual implementation/logic (such as, the
> implementation of importing datasets, creating projects, building models,
> and etc). Hence, these are similar to any other third-party library, which
> you have to invoke using their APIs. (They don't have main classes, they
> have APIs). This repo also contains a REST API, which exposes the
> above-mentioned APIs as a RESTful service. It also includes the source code
> for the UI, which invokes those REST APIs, behalf of the user. Please refer
> [1] to get the overall idea.
> Whereas, *product-ml* repo contains the source code, which collects the
> necessary libraries (such as the libraries of carbon-ml, REST API, UI) and
> bundles it all together, to create the final binary distribution.
>
> *carbon-ml* already contains the implementations of number of algorithms
> [2]. Your ultimate goal is to add three more such implementations to that
> repo (i.e: the three ensemble methods). In doing so, you don't need to
> re-implement the logics of importing datasets, creating projects and etc..
> As those have already been implemented and you can use those methods from
> their APIs. (Please refer any of the current algorithms to get an idea..).
>
> But, since it can be difficult to implement the ensemble logic and
> integrate it to carbon-ml repo, *at the same time*, We recommend you to *first
> implement your logic in a separate java client.* This has to be an
> independent maven project. The whole purpose of this java client is to
> implement your logic independently and test its functionality and accuracy.
> You can use native spark ml-lib libraries for this. In the java client,
> following steps needed to be done:
>
>- Read the CSV file.
>- Do the sampling as needed. (train set and test set)
>- Train an

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-04-25 Thread Supun Sethunga 
Hi Misgana,

As you progress, please keep us posted too. It would be nice if you
can share your code as well (Github project). You can take a fork of repo
[1], and start working on your fork.

[1] https://github.com/wso2/carbon-ml

On Mon, Apr 25, 2016 at 7:57 PM, Misgana Negassi <
negas...@tf.uni-freiburg.de> wrote:

> Hi Supun,
>
> Thank you for accepting me for this project!I am excited to work on it and
> start right away with the links you sent.
>
> Best,
> Misgana
>
>
>
> On 25.04.2016 12:06, Supun Sethunga wrote:
>
> 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> 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/
 [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]

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-03-23 Thread Supun Sethunga 
Hi Deng,

Looks good!. Please go ahead and submit to GSoC.

Regards,
Supun

On Thu, Mar 24, 2016 at 10:47 AM, tbc.dengwe...@outlook.com <
tbc.dengwe...@outlook.com> wrote:

> Hi Supun,
>
> Thansk for advise. I have added some figures. Have a look.
>
> https://drive.google.com/file/d/0BwujRZWY9rKPemVkbVYwTmd6bGM/view?usp=sharing
> thanks
> Deng
>
> --
> tbc.dengwe...@outlook.com
>
>
> *From:* Supun Sethunga 
> *Date:* 2016-03-23 22:11
> *To:* tbc.dengwe...@outlook.com
> *CC:* WSO2 Developers' List 
> *Subject:* Re: Re: [GSOC2016]Proposal 4: [ML] Ensemble Methods Support
> for WSO2 Machine Learner
> Hi Deng,
>
> Couple of comments:
>
>- Can you add sort of an architecture diagram, explaining your
>solution? (which visually explains implementation in a higher level)
>-
>- In the Road map, It makes more sense to mention the starting-date
>and end-date for each of the phases (instead of the duration). Also you can
>add time-slots for other steps (like doing the background research, code
>cleanup,  documenting and etc..) too, to the same timeline.
>
> Rest of the proposal looks good to me. :)
>
> Thanks,
> Supun
>
>
> On Wed, Mar 23, 2016 at 6:57 PM, tbc.dengwe...@outlook.com <
> tbc.dengwe...@outlook.com> wrote:
>
>> Hello supuns，
>> I have modified my modified my proposal. Please check it. The link is
>> below:
>> https://drive.google.com/open?id=0BwujRZWY9rKPemVkbVYwTmd6bGM
>> thanks
>> Deng.
>>
>> --
>> tbc.dengwe...@outlook.com
>>
>>
>> *From:* Supun Sethunga 
>> *Date:* 2016-03-23 02:35
>> *To:* tbcTobeContinued 
>> *CC:* Nirmal Fernando ; WSO2 Developers' List
>> 
>> *Subject:* Re: [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for
>> WSO2 Machine Learner
>> Hi,
>>
>> Thanks for your interest and the proposal. In the "Proposal 4: [ML]
>> Ensemble Methods Support for WSO2 Machine Learner", we are focusing on the
>> three methods: Bagging, Boosting and Stacking. You may not need to
>> implement several techniques for Boosting, but rather one technique for
>> each of the above three methods.
>>
>> Can you update the proposal accordingly?
>>
>> Thanks,
>> Supun
>>
>> On Tue, Mar 22, 2016 at 8:30 PM, Nirmal Fernando  wrote:
>>
>>> Thanks
>>>
>>> On Tue, Mar 22, 2016 at 8:22 PM, tbcTobeContinued <
>>> tbc.dengwe...@outlook.com> wrote:
>>>
 Sorry,here is the link:

 https://drive.google.com/file/d/0BwujRZWY9rKPemVkbVYwTmd6bGM/view?usp=sharing

 在 2016年3月22日，下午10:40，Nirmal Fernando  写道：

 Thanks for the proposal Deng, we'll check and provide feedback. It'll
 be easier, if you could share a google document with us, with comment
 rights.

 On Tue, Mar 22, 2016 at 7:42 PM, tbc.dengwe...@outlook.com <
 tbc.dengwe...@outlook.com> wrote:

> Hi,all
> I want to implemet AbaBoost for WSO2 Machine Leaner. here is my
> proposal, please give some feedback to improve it.
> Thanks
> wicky
>
> --
> tbc.dengwe...@outlook.com
>



 --

 Thanks & regards,
 Nirmal

 Team Lead - WSO2 Machine Learner
 Associate Technical Lead - Data Technologies Team, WSO2 Inc.
 Mobile: +94715779733
 Blog: http://nirmalfdo.blogspot.com/



>>>
>>>
>>> --
>>>
>>> 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
>>
>>
>
>
> --
> *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
___
Dev mailing list
Dev@wso2.org
http://wso2.org/cgi-bin/mailman/listinfo/dev

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-03-23 Thread Supun Sethunga 
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> 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/
>> [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
>>
>> Thanks,
>> Supun
>>
>> On Wed, Mar 23, 2016 at 7:20 AM, Nirmal Fernando < 
>> 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> 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/
>>>
>>>
>>>
>>
>>
>> --
>> *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
___
Dev mailing list
Dev@wso2.org
http://wso2.org/cgi-bin/mailman/listinfo/dev

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-03-23 Thread Supun Sethunga 
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> 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/
> [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
>
> Thanks,
> Supun
>
> On Wed, Mar 23, 2016 at 7:20 AM, Nirmal Fernando  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> 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/
>>
>>
>>
>
>
> --
> *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
___
Dev mailing list
Dev@wso2.org
http://wso2.org/cgi-bin/mailman/listinfo/dev

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-03-23 Thread Supun Sethunga 
Hi Deng,

Couple of comments:

   - Can you add sort of an architecture diagram, explaining your solution?
   (which visually explains implementation in a higher level)
   -
   - In the Road map, It makes more sense to mention the starting-date and
   end-date for each of the phases (instead of the duration). Also you can add
   time-slots for other steps (like doing the background research, code
   cleanup,  documenting and etc..) too, to the same timeline.

Rest of the proposal looks good to me. :)

Thanks,
Supun


On Wed, Mar 23, 2016 at 6:57 PM, tbc.dengwe...@outlook.com <
tbc.dengwe...@outlook.com> wrote:

> Hello supuns，
> I have modified my modified my proposal. Please check it. The link is
> below:
> https://drive.google.com/open?id=0BwujRZWY9rKPemVkbVYwTmd6bGM
> thanks
> Deng.
>
> --
> tbc.dengwe...@outlook.com
>
>
> *From:* Supun Sethunga 
> *Date:* 2016-03-23 02:35
> *To:* tbcTobeContinued 
> *CC:* Nirmal Fernando ; WSO2 Developers' List
> 
> *Subject:* Re: [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for
> WSO2 Machine Learner
> Hi,
>
> Thanks for your interest and the proposal. In the "Proposal 4: [ML]
> Ensemble Methods Support for WSO2 Machine Learner", we are focusing on the
> three methods: Bagging, Boosting and Stacking. You may not need to
> implement several techniques for Boosting, but rather one technique for
> each of the above three methods.
>
> Can you update the proposal accordingly?
>
> Thanks,
> Supun
>
> On Tue, Mar 22, 2016 at 8:30 PM, Nirmal Fernando  wrote:
>
>> Thanks
>>
>> On Tue, Mar 22, 2016 at 8:22 PM, tbcTobeContinued <
>> tbc.dengwe...@outlook.com> wrote:
>>
>>> Sorry,here is the link:
>>>
>>> https://drive.google.com/file/d/0BwujRZWY9rKPemVkbVYwTmd6bGM/view?usp=sharing
>>>
>>> 在 2016年3月22日，下午10:40，Nirmal Fernando  写道：
>>>
>>> Thanks for the proposal Deng, we'll check and provide feedback. It'll be
>>> easier, if you could share a google document with us, with comment rights.
>>>
>>> On Tue, Mar 22, 2016 at 7:42 PM, tbc.dengwe...@outlook.com <
>>> tbc.dengwe...@outlook.com> wrote:
>>>
 Hi,all
 I want to implemet AbaBoost for WSO2 Machine Leaner. here is my
 proposal, please give some feedback to improve it.
 Thanks
 wicky

 --
 tbc.dengwe...@outlook.com

>>>
>>>
>>>
>>> --
>>>
>>> Thanks & regards,
>>> Nirmal
>>>
>>> Team Lead - WSO2 Machine Learner
>>> Associate Technical Lead - Data Technologies Team, WSO2 Inc.
>>> Mobile: +94715779733
>>> Blog: http://nirmalfdo.blogspot.com/
>>>
>>>
>>>
>>
>>
>> --
>>
>> 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
>
>


-- 
*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

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-03-22 Thread Supun Sethunga 
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/
[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

Thanks,
Supun

On Wed, Mar 23, 2016 at 7:20 AM, Nirmal Fernando  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> 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/
>
>
>


-- 
*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

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-03-22 Thread Nirmal Fernando 
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> 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/
___
Dev mailing list
Dev@wso2.org
http://wso2.org/cgi-bin/mailman/listinfo/dev

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-03-22 Thread Supun Sethunga 
Hi,

Thanks for your interest and the proposal. In the "Proposal 4: [ML]
Ensemble Methods Support for WSO2 Machine Learner", we are focusing on the
three methods: Bagging, Boosting and Stacking. You may not need to
implement several techniques for Boosting, but rather one technique for
each of the above three methods.

Can you update the proposal accordingly?

Thanks,
Supun

On Tue, Mar 22, 2016 at 8:30 PM, Nirmal Fernando  wrote:

> Thanks
>
> On Tue, Mar 22, 2016 at 8:22 PM, tbcTobeContinued <
> tbc.dengwe...@outlook.com> wrote:
>
>> Sorry,here is the link:
>>
>> https://drive.google.com/file/d/0BwujRZWY9rKPemVkbVYwTmd6bGM/view?usp=sharing
>>
>> 在 2016年3月22日，下午10:40，Nirmal Fernando  写道：
>>
>> Thanks for the proposal Deng, we'll check and provide feedback. It'll be
>> easier, if you could share a google document with us, with comment rights.
>>
>> On Tue, Mar 22, 2016 at 7:42 PM, tbc.dengwe...@outlook.com <
>> tbc.dengwe...@outlook.com> wrote:
>>
>>> Hi,all
>>> I want to implemet AbaBoost for WSO2 Machine Leaner. here is my
>>> proposal, please give some feedback to improve it.
>>> Thanks
>>> wicky
>>>
>>> --
>>> tbc.dengwe...@outlook.com
>>>
>>
>>
>>
>> --
>>
>> Thanks & regards,
>> Nirmal
>>
>> Team Lead - WSO2 Machine Learner
>> Associate Technical Lead - Data Technologies Team, WSO2 Inc.
>> Mobile: +94715779733
>> Blog: http://nirmalfdo.blogspot.com/
>>
>>
>>
>
>
> --
>
> 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
___
Dev mailing list
Dev@wso2.org
http://wso2.org/cgi-bin/mailman/listinfo/dev

Re: [Dev] [GSOC2016]Proposal 4: [ML] Ensemble Methods Support for WSO2 Machine Learner

2016-03-22 Thread Nirmal Fernando 
Thanks for the proposal Deng, we'll check and provide feedback. It'll be
easier, if you could share a google document with us, with comment rights.

On Tue, Mar 22, 2016 at 7:42 PM, tbc.dengwe...@outlook.com <
tbc.dengwe...@outlook.com> wrote:

> Hi,all
> I want to implemet AbaBoost for WSO2 Machine Leaner. here is my proposal,
> please give some feedback to improve it.
> Thanks
> wicky
>
> --
> tbc.dengwe...@outlook.com
>



-- 

Thanks & regards,
Nirmal

Team Lead - WSO2 Machine Learner
Associate Technical Lead - Data Technologies Team, WSO2 Inc.
Mobile: +94715779733
Blog: http://nirmalfdo.blogspot.com/
___
Dev mailing list
Dev@wso2.org
http://wso2.org/cgi-bin/mailman/listinfo/dev