...
The factory foreman of the Sweet Factory needs to predict the nature of next shipment of sugar syrup based on the shipments he has received so far. A predictive solution has been trained with inputs, temperature and density of the latest shipment. Using these, a prediction is required on whether the shipment received meets his requirements before it is dispatched to the factory. We can also assume that this pre-trained model is exported in PMML serialization and that it is available in the system. To build and train a model, you can use this PMML sample.
| Tip | ||||
|---|---|---|---|---|
| ||||
PMML (Predictive Model Markup Language) is a standardized serialization that is used for exporting predictive solutions (machine learning models). PMML works by defining the model in one system and transferring the model to a different system via an XML file. This allows predictions to be made using events from the new system. This XML file can contain various data transformation and preprocessing steps in addition to one or more predictive models. In addition to PMML, TensorFlow serialization is also supported by Stream Processor for static real-time predictions. For more details, see Siddhi Extensions Documentation - Tensorflow. |
...