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There are two possible Siddhi query syntaxes to use the extension in an execution plan as follows.
< double | float|long|int|string|boolean >predict(<string>pathToMLModel, <string> dataType)- Extension Type: StreamProcessor
- Description: Returns an output event with the additional attribute with the response variable name of the model, set with the predicted value, using the feature values extracted from the input event.
- Parameter: pathToMLModel: The file path or the registry path where ML model is located. If the model storage location is registry, the value of this this parameter should have the prefix “
registry:” Parameter: dataType: Data type of the predicted value (double, float, long, integer/int, string, boolean/bool).
Example:
predict(‘registry:/_system/governance/mlmodels/indian-diabetes-model’)
< double | float|long|int|string|boolean >predict(<string>pathToMLModel, <string> dataType,<double>input)- Extension Type: StreamProcessor
- Description: Returns an output event with the additional attribute with the response variable name of the model, set with the predicted value, using the feature values extracted from the input event.
- Parameter: pathToMLModel: The file path or the registry path where ML model is located. If the model storage location is registry, the value of this parameter should have the prefix “
registry:” Parameter: dataType: Data type of the predicted value (double, float, long, integer/int, string, boolean/bool).
Parameter : input: A variable attribute value of the input stream which is sent to the ML model as feature values for predictions. Function does not accept any constant values as input parameters. You can have multiple input parameters.
Example:
predict(‘registry:/_system/governance/mlmodels/indian-diabetes-model’, NumPregnancies, TSFT, DPF, BMI, DBP, PG2, Age, SI2)
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- Install the WSO2 Machine Learner (ML) Features. For detailed instructions to install WSO2 ML features, see Installing Machine Learner Features.
Creating the input stream
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