Properties of Trainable Evaluator window
If you want quick and good generic extraction results with a relatively small training set, the highly optimizable Trainable
Evaluator, is recommended. This evaluator is used to compare alternatives from other locators to determine which of those
alternatives match a specific set of criteria. This evaluator relies on alternatives from the input locator. It also learns from
false alternatives to improve training.
The extraction type of a Trainable Evaluator is "group" which means that this evaluator returns multiple subfields. No subfields are created automatically, so it is necessary to create one or more subfields. Once subfields are added select one or more fields individually using the links or you can click the Create and Assign Fields button to create and assign all fields at once.
The Properties of Trainable Evaluator window has the following tabs:
Related topics:
-
More information about configuring a Trainable Evaluator