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A data science model stored in a PFA format. This could either be a JSON or a YAML file extension.
Installing the PFA plug-in. (This can be downloaded from Yellowfin’s Marketplace.)
Data that you wish the model to run on.
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- Save your model in the PFA (.json/.yaml) format.
- Build a Yellowfin report with data you wish to generate predictions for.
- Drag in a new column that is of the same data type as the prediction to be generated. For example, if your model returns a categorical prediction such as gender, you would want to use a text dimension.
- Within the column formatting drop-down, click Advanced Function.
- Select the Statistical option from the drop-down and select the feature you wish to usePFA option. Further configuration settings will appear on doing so.
- Provide the full filepath or URL to the PFA file and click Load. If the file path has not been correctly specified, you will need to click Reset, adjust the path, and click Load again.
. - Specify the extension of the uploaded PFA file by choosing either the YAML or JSON option.
- Then choose the Load option. If Yellowfin is able to load the specified file, detailed configuration options will appear.
- Match the input columns required by your model, with the appropriate columns in the Yellowfin report.
. These fields will be labeled as the name of the variable, but if no name is specified in the PFA file, then the variable type shows up, as shown in this example.
- Then select the output field.
- Click the Save button on the top-right corner of the advanced function window.
Click Save. - Note: If there was a problem in processing the file, check that you have provided valid columns of the same data type required by the model, or look at the yellowfin.log file for a complete error description.
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