知微
fa45d8aa5f
- health_checklist.json: 192.168.1.122→node122
- ocr_client.py: docstring IP→node122
- docs/market-data-requirements.md: IP→node122
- 所有API调用通过ProxyHandler({})绕过系统代理
Privoxy对node122:18003返回500，直连正常
36 lines
1.2 KiB
Plaintext
36 lines
1.2 KiB
Plaintext
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=====================================================
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PAICE's evaluation statistics for stemming algorithms
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=====================================================
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Given a list of words with their real lemmas and stems according to stemming algorithm under evaluation,
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counts Understemming Index (UI), Overstemming Index (OI), Stemming Weight (SW) and Error-rate relative to truncation (ERRT).
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>>> from nltk.metrics import Paice
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-------------------------------------
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Understemming and Overstemming values
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-------------------------------------
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>>> lemmas = {'kneel': ['kneel', 'knelt'],
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... 'range': ['range', 'ranged'],
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... 'ring': ['ring', 'rang', 'rung']}
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>>> stems = {'kneel': ['kneel'],
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... 'knelt': ['knelt'],
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... 'rang': ['rang', 'range', 'ranged'],
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... 'ring': ['ring'],
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... 'rung': ['rung']}
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>>> p = Paice(lemmas, stems)
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>>> p.gumt, p.gdmt, p.gwmt, p.gdnt
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(4.0, 5.0, 2.0, 16.0)
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>>> p.ui, p.oi, p.sw
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(0.8..., 0.125..., 0.15625...)
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>>> p.errt
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1.0
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>>> [('{0:.3f}'.format(a), '{0:.3f}'.format(b)) for a, b in p.coords]
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[('0.000', '1.000'), ('0.000', '0.375'), ('0.600', '0.125'), ('0.800', '0.125')]
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