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Natural Language Processing with Java and LingPipe Cookbook by Krishna Dayanidhi, Breck Baldwin

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Classifier-building life cycle

At the top-level building, a classifier usually proceeds as follows:

  1. Create training data—refer to the following recipe for more about this.
  2. Build training and evaluation infrastructure with sanity check.
  3. Establish baseline performance.
  4. Select optimization metric for classifier—this is what the classifier is trying to do and will guide tuning.
  5. Optimize classifier via techniques such as:
    • Parameter tuning
    • Thresholding
    • Linguistic tuning
    • Adding training data
    • Refining classifier definition

This recipe will present the first four steps in concrete terms, and there are recipes in this chapter for the optimization step.

Getting ready

Nothing happens without training data for classifiers. Look at the Annotation recipe at the end of the ...

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