Hi,
We are in the process of implementing a CEP extension for Machine Learner
Predictions. This extension allows the machine learning models generated by
WSO2 ML to be used within CEP for predictions.
To use this, following ML features need to be installed in CEP.
- Machine Learner Core feature
- Machine Learner Commons feature
- Machine Learner Database Service feature
This extension is implemented as a *StreamProcessor*.
*The syntax :*
There are two possible ways to use the extension.
*<stream-name>#ml:predict(‘<path-to-ML-model>’) *
*<stream-name>#ml:predict('<path-to-ML-model>', attribute 1, attribute 2,
.......)*
*path-to-MLModel*
The storage location of the Machine learning model can be either registry
or file system.
If the model is stored in the registry, *path-to-ML-model* should have the
prefix *registry:*
If the model is stored in the file system, *path-to-ML-model* should have
the prefix *file:*
*attribute 1, attribute 2, ….*
These are the attribute names of the stream. The values of these attributes
are sent to the MLModel as feature input values. When the attribute names
are not explicitly given, the extension will map the attribute names of the
stream with the feature names of the ML model.
The output events will contain the attribute* prediction* which holds the
prediction result for that particular event.
Thanks.
--
Manorama Perera
Software Engineer
WSO2, Inc.; http://wso2.com/
Mobile : +94716436216
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