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Entropy Guided Transformation Learning: Algorithms and Applications: Algorithms and Applications (Springer Briefs in Computer Science) - Couverture souple
Synopsis
Entropy Guided Transformation Learning: Algorithms and Applications (ETL) presents a machine learning algorithm for classification tasks. ETL generalizes Transformation Based Learning (TBL) by solving the TBL bottleneck: the construction of good template sets. ETL automatically generates templates using Decision Tree decomposition. The authors describe ETL Committee, an ensemble method that uses ETL as the base learner. Experimental results show that ETL Committee improves the effectiveness of ETL classifiers. The application of ETL is presented to four Natural Language Processing (NLP) tasks: part-of-speech tagging, phrase chunking, named entity recognition and semantic role labeling. Extensive experimental results demonstrate that ETL is an effective way to learn accurate transformation rules, and shows better results than TBL with handcrafted templates for the four tasks. By avoiding the use of handcrafted templates, ETL enables the use of transformation rules to a greater range of tasks. Suitable for both advanced undergraduate and graduate courses, Entropy Guided Transformation Learning: Algorithms and Applications provides a comprehensive introduction to ETL and its NLP applications.
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Entropy Guided Transformation Learning: Algorithms and Applications
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Springer London, 2012
ISBN 10 : 1447129776
ISBN 13 : 9781447129776
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Entropy Guided Transformation Learning: Algorithms and Applications
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Entropy Guided Transformation Learning: Algorithms and Applications (SpringerBriefs in Computer Science)
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Entropy Guided Transformation Learning: Algorithms and Applications
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Springer London Mrz 2012, 2012
ISBN 10 : 1447129776
ISBN 13 : 9781447129776
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Entropy Guided Transformation Learning: Algorithms and Applications (ETL) presents a machine learning algorithm for classification tasks. ETL generalizes Transformation Based Learning (TBL) by solving the TBL bottleneck: the construction of good template sets. ETL automatically generates templates using Decision Tree decomposition.The authors describe ETL Committee, an ensemble method that uses ETL as the base learner. Experimental results show that ETL Committee improves the effectiveness of ETL classifiers. The application of ETL is presented to four Natural Language Processing (NLP) tasks: part-of-speech tagging, phrase chunking, named entity recognition and semantic role labeling. Extensive experimental results demonstrate that ETL is an effective way to learn accurate transformation rules, and shows better results than TBL with handcrafted templates for the four tasks. By avoiding the use of handcrafted templates, ETL enables the use of transformation rules to a greater range of tasks.Suitable for both advanced undergraduate and graduate courses, Entropy Guided Transformation Learning: Algorithms and Applications provides a comprehensive introduction to ETL and its NLP applications. 92 pp. Englisch. N° de réf. du vendeur 9781447129776
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Entropy Guided Transformation Learning: Algorithms and Applications
Edité par
Springer London, Springer London, 2012
ISBN 10 : 1447129776
ISBN 13 : 9781447129776
Neuf
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Entropy Guided Transformation Learning: Algorithms and Applications (ETL) presents a machine learning algorithm for classification tasks. ETL generalizes Transformation Based Learning (TBL) by solving the TBL bottleneck: the construction of good template sets. ETL automatically generates templates using Decision Tree decomposition.The authors describe ETL Committee, an ensemble method that uses ETL as the base learner. Experimental results show that ETL Committee improves the effectiveness of ETL classifiers. The application of ETL is presented to four Natural Language Processing (NLP) tasks: part-of-speech tagging, phrase chunking, named entity recognition and semantic role labeling. Extensive experimental results demonstrate that ETL is an effective way to learn accurate transformation rules, and shows better results than TBL with handcrafted templates for the four tasks. By avoiding the use of handcrafted templates, ETL enables the use of transformation rules to a greater range of tasks.Suitable for both advanced undergraduate and graduate courses, Entropy Guided Transformation Learning: Algorithms and Applications provides a comprehensive introduction to ETL and its NLP applications. N° de réf. du vendeur 9781447129776
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Entropy Guided Transformation Learning: Algorithms and Applications
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Springer London, Springer London Mär 2012, 2012
ISBN 10 : 1447129776
ISBN 13 : 9781447129776
Neuf
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Taschenbuch. Etat : Neu. Neuware -Entropy Guided Transformation Learning: Algorithms and Applications (ETL) presents a machine learning algorithm for classification tasks. ETL generalizes Transformation Based Learning (TBL) by solving the TBL bottleneck: the construction of good template sets. ETL automatically generates templates using Decision Tree decomposition.The authors describe ETL Committee, an ensemble method that uses ETL as the base learner. Experimental results show that ETL Committee improves the effectiveness of ETL classifiers. The application of ETL is presented to four Natural Language Processing (NLP) tasks: part-of-speech tagging, phrase chunking, named entity recognition and semantic role labeling. Extensive experimental results demonstrate that ETL is an effective way to learn accurate transformation rules, and shows better results than TBL with handcrafted templates for the four tasks. By avoiding the use of handcrafted templates, ETL enables the use of transformation rules to a greater range of tasks.Suitable for both advanced undergraduate and graduate courses, Entropy Guided Transformation Learning: Algorithms and Applications provides a comprehensive introduction to ETL and its NLP applications.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 92 pp. Englisch. N° de réf. du vendeur 9781447129776
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Entropy Guided Transformation Learning : Algorithms and Applications
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Entropy Guided Transformation Learning: Algorithms and Applications
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Springer London Ltd, 2012
ISBN 10 : 1447129776
ISBN 13 : 9781447129776
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Entropy Guided Transformation Learning : Algorithms and Applications
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Entropy Guided Transformation Learning : Algorithms and Applications
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Springer, 2012
ISBN 10 : 1447129776
ISBN 13 : 9781447129776
Ancien ou d'occasion
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
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