[jira] [Updated] (SYSTEMML-983) Add mllearn and scala wrappers for GLM

["Janardhan (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SYSTEMML-983?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Janardhan updated SYSTEMML-983:
-------------------------------
    Labels: beginner newbie starter  (was: )

> Add mllearn and scala wrappers for GLM
> --------------------------------------
>
>                 Key: SYSTEMML-983
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-983
>             Project: SystemML
>          Issue Type: Task
>          Components: APIs
>            Reporter: Niketan Pansare
>            Priority: Major
>              Labels: beginner, newbie, starter
>
> See https://apache.github.io/incubator-systemml/algorithms-regression.html#generalized-linear-models for usage
> Since this is a starter task, I describe the steps to complete this task:
> 1. Implement a scala class (which inherits from BaseSystemMLRegressor) similar to https://github.com/apache/incubator-systemml/blob/master/src/main/scala/org/apache/sysml/api/ml/LinearRegression.scala
> 2. Modify getTrainingScript and getPredictionScript to specify the parameters used. See the algorithm documentation for these parameters.
> 3. Ensure that you implement appropriate traits to accept hyperparameters (eg: HasLaplace, HasIcpt, HasRegParam, HasTol, etc). These traits are available at https://github.com/apache/incubator-systemml/blob/master/src/main/scala/org/apache/sysml/api/ml/BaseSystemMLClassifier.scala#L36
> 4. Implement a python class (that extends BaseSystemMLRegressor) with constructor similar to https://github.com/apache/incubator-systemml/blob/master/src/main/python/systemml/mllearn/estimators.py#L218 which essentially accepts the hyperparameters and invokes the scala side methods (example:  self.estimator.setLaplace(laplace))
> 5. Update the algorithm documentation by specifying the usage as well as examples.



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