Scoring records

Earlier, you scored the records that were used to estimate the model so that you could evaluate how accurate the model was. This example scores a different set of records from the ones used to create the model. Evaluating accuracy is one of the goals of modeling with a target field. You study records for which you know the outcome to identify patterns so that you can predict outcomes that you don't yet know.

You can update the existing Data Asset or Import node to point to a different data file. Or you can add a Data Asset or Import node that reads in the data you want to score. Either way, the new data set must contain the same input fields that are used by the model (Age, Income level, Education, and so on), but not the target field Credit rating.

Alternatively, you can add the model nugget to any flow that includes the expected input fields. Whether read from a file or a database, the source type does not matter if the field names and types match the ones that are used by the model.