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https://issues.apache.org/jira/browse/SPARK-3251?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Christoph Sawade updated SPARK-3251:
------------------------------------
Description:
*Make threshold mandatory*
Currently, the output of predict for an example is either the score
or the class. This side-effect is caused by clearThreshold. To
clarify that behaviour three different types of predict (predictScore,
predictClass, predictProbabilty) were introduced; the threshold is not
longer optional.
*Clarify classification interfaces*
Currently, some functionality is spreaded over multiple models.
In order to clarify the structure and simplify the implementation of
more complex models (like multinomial logistic regression), two new
classes are introduced:
- BinaryClassificationModel: for all models that derives a binary
classification from a single weight vector. Comprises the tresholding
functionality to derive a prediction from a score. It basically captures
SVMModel and LogisticRegressionModel.
- ProbabilitistClassificaitonModel: This trait defines the interface for models
that return a calibrated confidence score (aka probability).
*Misc*
- some renaming
- add test for probabilistic output
was:
** Make threshold mandatory
Currently, the output of predict for an example is either the score
or the class. This side-effect is caused by clearThreshold. To
clarify that behaviour three different types of predict (predictScore,
predictClass, predictProbabilty) were introduced; the threshold is not
longer optional.
** Clarify classification interfaces
Currently, some functionality is spreaded over multiple models.
In order to clarify the structure and simplify the implementation of
more complex models (like multinomial logistic regression), two new
classes are introduced:
- BinaryClassificationModel: for all models that derives a binary
classification from a single weight vector. Comprises the tresholding
functionality to derive a prediction from a score. It basically captures
SVMModel and LogisticRegressionModel.
- ProbabilitistClassificaitonModel: This trait defines the interface for models
that return a calibrated confidence score (aka probability).
** Misc
- some renaming
- add test for probabilistic output
> Clarify learning interfaces
> ----------------------------
>
> Key: SPARK-3251
> URL: https://issues.apache.org/jira/browse/SPARK-3251
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.1.0, 1.1.1
> Reporter: Christoph Sawade
>
> *Make threshold mandatory*
> Currently, the output of predict for an example is either the score
> or the class. This side-effect is caused by clearThreshold. To
> clarify that behaviour three different types of predict (predictScore,
> predictClass, predictProbabilty) were introduced; the threshold is not
> longer optional.
> *Clarify classification interfaces*
> Currently, some functionality is spreaded over multiple models.
> In order to clarify the structure and simplify the implementation of
> more complex models (like multinomial logistic regression), two new
> classes are introduced:
> - BinaryClassificationModel: for all models that derives a binary
> classification from a single weight vector. Comprises the tresholding
> functionality to derive a prediction from a score. It basically captures
> SVMModel and LogisticRegressionModel.
> - ProbabilitistClassificaitonModel: This trait defines the interface for
> models that return a calibrated confidence score (aka probability).
> *Misc*
> - some renaming
> - add test for probabilistic output
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