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https://issues.apache.org/jira/browse/SYSTEMML-987?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Niketan Pansare updated SYSTEMML-987:
-------------------------------------
Description:
See
https://apache.github.io/incubator-systemml/algorithms-classification.html#decision-trees
for usage.
Since this is a starter task, I describe the steps to complete this task:
1. Implement a scala class (which inherits from BaseSystemMLClassifier) similar
to
https://github.com/apache/incubator-systemml/blob/master/src/main/scala/org/apache/sysml/api/ml/NaiveBayes.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 BaseSystemMLClassifier) with
constructor similar to
https://github.com/apache/incubator-systemml/blob/master/src/main/python/systemml/mllearn/estimators.py#L284
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-classification.html#decision-trees
for usage.
Since this is a starter task, I describe steps to complete this task:
1. Implement a scala class (which inherits from BaseSystemMLClassifier) similar
to
https://github.com/apache/incubator-systemml/blob/master/src/main/scala/org/apache/sysml/api/ml/NaiveBayes.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 BaseSystemMLClassifier) with
constructor similar to
https://github.com/apache/incubator-systemml/blob/master/src/main/python/systemml/mllearn/estimators.py#L284
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.
> Add mllearn and scala wrappers for decision tree
> -------------------------------------------------
>
> Key: SYSTEMML-987
> URL: https://issues.apache.org/jira/browse/SYSTEMML-987
> Project: SystemML
> Issue Type: Task
> Components: APIs
> Reporter: Niketan Pansare
> Labels: Hacktoberfest, starter
>
> See
> https://apache.github.io/incubator-systemml/algorithms-classification.html#decision-trees
> for usage.
> Since this is a starter task, I describe the steps to complete this task:
> 1. Implement a scala class (which inherits from BaseSystemMLClassifier)
> similar to
> https://github.com/apache/incubator-systemml/blob/master/src/main/scala/org/apache/sysml/api/ml/NaiveBayes.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 BaseSystemMLClassifier) with
> constructor similar to
> https://github.com/apache/incubator-systemml/blob/master/src/main/python/systemml/mllearn/estimators.py#L284
> 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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