Natural Language Annotation for Machine Learning by James Pustejovsky & Amber Stubbs

Natural Language Annotation for Machine Learning by James Pustejovsky & Amber Stubbs

Author:James Pustejovsky & Amber Stubbs [James Pustejovsky and Amber Stubbs]
Language: eng
Format: epub, pdf
Tags: COMPUTERS / Natural Language Processing
ISBN: 9781449307646
Publisher: O'Reilly Media
Published: 2012-10-10T16:00:00+00:00


We won’t be going into detail about these, however; other books on machine learning (see the list at the start of the chapter) provide excellent guides for how these classifiers work, and the ones we’ve already discussed are enough to get you started in training algorithms on your annotated data.

Micro Versus Macro

Classifiers are evaluated using the results of a simple table that sums up how often the tags were correctly assigned. From this table we can compute the accuracy of the classifier. Recall from Evaluate the Results that we use four measures:

Accuracy



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