The predictive model is an algorithm that you apply to streaming data to predict outcomes. In GoldenGate Stream Analytics, a predictive model is a PMML file, that you upload and store in the system. GGSA supports PMML versions 3.0, 3.1, 3.2, 4.0, and 4.1. In a pipeline, you use a predictive model in a scoring stage to do probability scoring.
12.1 Importing a Predictive Model
- On the Catalog page, click Create New Item, and select Predictive Model from the drop-down list.
- On the Type Properties screen, enter the following details:
- Connection Type: Select Kafka, from the drop-down list.
- Under Type Properties do the following and then click Next:
- Under Predictive Model Details, do the following and click Save:
- For Predictive Model URL, upload your PMML file.
- In the Model Version field, enter the version of this artifact. For example,
- (Optional) In the Version Description, enter a meaningful description for your PMML file.
- In the Algorithm field, accept the default. The algorithm is derived from the PMML file you have uploaded.
- (Optional) In the Tool drop-down list, select the tool with which you created your PMML file.
12.2 Adding a Scoring Stage
- Open the required pipeline in Pipeline Editor.
- Right-click the stage after which you want to add a scoring stage, click Add a Stage, and then select Scoring.
- Enter a meaningful name and suitable description for the scoring stage and click Save.
- In the stage editor, enter the following details:
- Model name: Select the predictive model that you want to use in the scoring stage
- Model Version: Select the version of the predictive model
- Mapping: Select the corresponding model fields that appropriately map to the stage fields