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From "Tsuyoshi Ozawa" <ozawa.tsuyo...@lab.ntt.co.jp>
Subject RE: Open tasks: Integration with MLPipeline
Date Thu, 17 Dec 2015 01:16:54 GMT
Hi Niketan,

The jira for SystemML seems to be open now:
https://issues.apache.org/jira/browse/SYSTEMML

Do you mind creating issue for the tasks? We can avoid conflicts of assignee
by using JIRA.

Thanks,
- Tsuyoshi


-----Original Message-----
From: Glenn Weidner [mailto:gweidner@us.ibm.com] 
Sent: Tuesday, December 15, 2015 5:28 AM
To: dev@systemml.incubator.apache.org
Cc: npansar@us.ibm.com
Subject: Re: Open tasks: Integration with MLPipeline

Hi,

I'm interested in working on item 4:

4. Add MLPipeline wrappers for existing scripts.
- Refer to
https://github.com/apache/incubator-systemml/tree/master/scripts/algorithms
to pick the algorithm and
http://apache.github.io/incubator-systemml/algorithms-reference.html to
understand the assumptions as well as parameters to the given algorithm.
- A good algorithm to start with is L2SVM:
http://apache.github.io/incubator-systemml/algorithms-classification.html#bi
nary-class-support-vector-machines
https://github.com/apache/incubator-systemml/blob/master/scripts/algorithms/
l2-svm.dml
https://github.com/apache/incubator-systemml/blob/master/scripts/algorithms/
l2-svm-predict.dml

Thanks,
Glenn


Niketan Pansare---12/03/2015 02:32:50 PM---Hi all, In this email, I list the
open tasks related to integration with

From: Niketan Pansare/Almaden/IBM@IBMUS
To: dev@systemml.incubator.apache.org
Cc: "Tatsuya Nishiyama" <nishiyama.tatsuya@lab.ntt.co.jp>
Date: 12/03/2015 02:32 PM
Subject: Open tasks: Integration with MLPipeline

________________________________






Hi all,

In this email, I list the open tasks related to integration with MLPipeline.
This allows external developers to contribute to the SystemML project until
our JIRA server is up and running.

1. Make the existing Logistic regression wrapper more robust:
- Extend the wrapper or the DML script to handle zero-based labels (either
throw an error or support zero-based labels).

2. Improve the performance of the Logistic regression wrapper:
- Profile the wrapper to find potential bottlenecks. The candidates for
bottlenecks are RDDConverterUtilsExt.vectorDataFrameToBinaryBlock and line
153-158 in LogisticRegressionModel.

3.  Perform detailed performance analysis of the converter utils.
- Also explore the usability aspect of these utils.

4. Add MLPipeline wrappers for existing scripts.
- Refer to
https://github.com/apache/incubator-systemml/tree/master/scripts/algorithms
to pick the algorithm and
http://apache.github.io/incubator-systemml/algorithms-reference.html to
understand the assumptions as well as parameters to the given algorithm.
- A good algorithm to start with is L2SVM:
http://apache.github.io/incubator-systemml/algorithms-classification.html#bi
nary-class-support-vector-machines
https://github.com/apache/incubator-systemml/blob/master/scripts/algorithms/
l2-svm.dml
https://github.com/apache/incubator-systemml/blob/master/scripts/algorithms/
l2-svm-predict.dml

5. Add the documentation for MLPipeline wrappers to
http://apache.github.io/incubator-systemml/index.html

References:
1. Existing Logistic regression wrappers:
https://github.com/apache/incubator-systemml/blob/master/src/main/java/org/a
pache/sysml/api/ml/LogisticRegression.java
https://github.com/apache/incubator-systemml/blob/master/src/main/java/org/a
pache/sysml/api/ml/LogisticRegressionModel.java

2. Converter utils:
https://github.com/apache/incubator-systemml/blob/master/src/main/java/org/a
pache/sysml/runtime/instructions/spark/utils/RDDConverterUtilsExt.java

Thanks,

Niketan Pansare
IBM Almaden Research Center
E-mail: npansar At us.ibm.com
http://researcher.watson.ibm.com/researcher/view.php?person=us-npansar






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