Recognizer Types

Object Class Recognition supports three different types of recognizer. All three use neural networks but have different characteristics.

Before you train a recognizer you can also choose how many training iterations to run. Increasing the number of iterations improves the training and results in better accuracy, but each additional iteration that you add has a smaller effect.

To find the optimum number of iterations, Micro Focus recommends that you start with a small number of iterations. Double the number of iterations each time you train, until accuracy is acceptable. As a general rule, good accuracy can be obtained by multiplying the number of object classes in the recognizer by 2000.


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