Chapter 14: Fundamentals of Model Measurement
14.1. Introduction to Model Measurement
14.2. Use of a Gold Standard Corpus
14.3. Setup of a Gold Standard Corpus
14.4. Setup of Approximate Annotations
14.5. Creation of Samples for Development and Testing
14.6. Model Quality and Decisions
14.6.1. Strategies for Overcoming Low Recall
14.6.2. Strategies for Overcoming Low Precision
14.1. Introduction to Model Measurement
Measuring the quality of your models for information extraction (IE) usually means leveraging the metrics of recall, precision, and potentially F-measure as introduced in chapter 1. You may remember that precision is the ratio of the number of correctly labeled spans to the total that ...
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