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Two-Stage P-R Maximization (Errata- Lexicon+MaxPR -10 @2017/04/26)

Two-Stage P-R Maximization (Errata- Lexicon+MaxPR -10 @2017/04/26). Why two stage? No simple analytical decision rules that are capable of achieving any user-specified criterion function of precision and recall … Error : If mimimum error => Correction : If minimum error => or.

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Two-Stage P-R Maximization (Errata- Lexicon+MaxPR -10 @2017/04/26)

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  1. Two-Stage P-R Maximization(Errata- Lexicon+MaxPR -10 @2017/04/26) • Why two stage? • No simple analytical decision rules that are capable of achieving any user-specified criterion function of precision and recall • … • Error: • If mimimum error => • Correction: • If minimum error => • or Jing-Shin Chang, EE, National Tsing-Hua University

  2. MinErr Classifier: Two-Class Classifier forIdentifying New Words or Compound Words • Input: n-grams (n-word compounds, n-character words) in the text corpus • Output: assign a class label ("word" or "non-word") to each n-gram • Classifier: a log-likelihood ratio (LLR) tester (minimum error classifier) • Decision Rules: • Advantage: ensure minimum classification error (with 0 =0) if the distributions are known. Jing-Shin Chang, EE, National Tsing-Hua University

  3. Filter: Two-Class Classifier (Log-Likelihood Ratio Ranking Module) • Input: n-grams in the unsegmented text corpus • Output: assign a class label ("word" or "non-word") to each n-gram • Classifier: a log-likelihood ratio (LLR) tester (minimum error classifier) • Decision Rules: • Advantage: ensure minimum classification error (with 0 =0) if the distributions are known. Jing-Shin Chang, EE, National Tsing-Hua University

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