Entropy Guided Transformation Learning: Algorithms and Applications (SpringerBriefs in Computer Science) Tapa blanda - 2012 - 2012th Edición
de Santos, Cícero Nogueira dos; Milidiú, Ruy Luiz
Descripción de contraportada
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.
Detalles
- Título Entropy Guided Transformation Learning: Algorithms and Applications (SpringerBriefs in Computer Science)
- Autor Santos, Cícero Nogueira dos; Milidiú, Ruy Luiz
- Encuadernación Tapa blanda
- Número de edición 2012th
- Edición 2012
- Idioma ENG
- Editorial Springer
- Fecha de publicación 2012-03
- ISBN 9781447129776
-
Temas
- Aspects (Academic): Science/Technology Aspects
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Entropy Guided Transformation Learning: Algorithms and Applications (SpringerBriefs in Computer Science)
de dos Santos, CÃcero Nogueira; Milidiú, Ruy Luiz
- Nuevo
- Tapa blanda
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