Jiayun han (9 risultati)
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 65,01
EUR 3,50 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: New.
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 75,14
EUR 11,74 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: Brand New. 68 pages. 8.66x5.91x0.16 inches. In Stock.
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Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 36,35
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Develop a Part-of-Speech Tagger and a Tagger-Maker | Algorithms, Implementations, Results, and APIs | Jiayun Han | Taschenbuch | 68 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659376221 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osn…abrück, mail[at]preigu[dot]de | Anbieter: preigu.
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- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 39,90
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This project is aimed to build an efficient, scalable, portable, and trainable part-of-speech tagger. Using 98% of Penn Treebank-3 as the training data, it builds a raw tagger, using Bayes' theorem, a hidden Markov model, and the V…iterbi algorithm. After that, a reinforcement machine learning algorithm and contextual transformation rules were applied to increase the tagger's accuracy. The tagger's final accuracy on the testing data is 96.51% and its speed is about 26,000 words per second on a computer with two-gigabyte random access memory and two 3.00 GHz Pentium duo processors. The tagger's portability and trainability are proved by the tagger-maker's success in building a new tagger out of a corpus that is annotated with the tagset different from that of Penn Treebank. 68 pp. Englisch.
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- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 65,02
EUR 7,63 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand.
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- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 65,18
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND.
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- Print on Demand
Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 34,25
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Han JiayunJiayun Han, Obtained his PhD in Linguistics and MS in Artificial Intelligence from The University of Georgia, U.S.A. He was working for North Side Inc. as a natural language processing engine…er and is currently employed by .
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- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 39,90
EUR 60,60 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This project is aimed to build an efficient, scalable, portable, and trainable part-of-speech tagger. Using 98% of Penn Treebank-3 as the training data, it builds a raw tagger, using Bayes' theorem, a hidden Markov model, and the Viterb…i algorithm. After that, a reinforcement machine learning algorithm and contextual transformation rules were applied to increase the tagger's accuracy. The tagger's final accuracy on the testing data is 96.51% and its speed is about 26,000 words per second on a computer with two-gigabyte random access memory and two 3.00 GHz Pentium duo processors. The tagger's portability and trainability are proved by the tagger-maker's success in building a new tagger out of a corpus that is annotated with the tagset different from that of Penn Treebank.
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- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 39,90
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This project is aimed to build an efficient, scalable, portable, and trainable part-of-speech tagger. Using 98% of Penn Treebank-3 as the training data, it builds a raw tagger, using Bayes' theorem, a hidden Markov model, and the Viter…bi algorithm. After that, a reinforcement machine learning algorithm and contextual transformation rules were applied to increase the tagger's accuracy. The tagger's final accuracy on the testing data is 96.51% and its speed is about 26,000 words per second on a computer with two-gigabyte random access memory and two 3.00 GHz Pentium duo processors. The tagger's portability and trainability are proved by the tagger-maker's success in building a new tagger out of a corpus that is annotated with the tagset different from that of Penn Treebank.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch.
