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Posted to issues@systemml.apache.org by "Niketan Pansare (JIRA)" <ji...@apache.org> on 2016/09/29 19:13:20 UTC
[jira] [Updated] (SYSTEMML-983) Add mllearn and scala wrappers for
GLM
[ https://issues.apache.org/jira/browse/SYSTEMML-983?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Niketan Pansare updated SYSTEMML-983:
-------------------------------------
Description:
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.
was:See https://apache.github.io/incubator-systemml/algorithms-regression.html#generalized-linear-models for usage
> 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
>
> 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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