Scientific Data Mining and Knowledge Discovery Principles and Foundations /

With the evolution in data storage, large databases have stimulated researchers from many areas, especially machine learning and statistics, to adopt and develop new techniques for data analysis in different fields of science. In particular, there have been notable successes in the use of statistica...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Gaber, Mohamed Medhat (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010.
Edición:1st ed. 2010.
Temas:
Data mining.
Mathematics-Data processing.
Artificial intelligence.
Pattern recognition systems.
Chemistry-Data processing.
Earth sciences.
Data Mining and Knowledge Discovery.
Computational Science and Engineering.
Artificial Intelligence.
Automated Pattern Recognition.
Computational Chemistry.
Earth Sciences.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Background
  • Machine Learning
  • Statistical Inference
  • The Philosophy of Science and its relation to Machine Learning
  • Concept Formation in Scientific Knowledge Discovery from a Constructivist View
  • Knowledge Representation and Ontologies
  • Computational Science
  • Spatial Techniques
  • Computational Chemistry
  • String Mining in Bioinformatics
  • Data Mining and Knowledge Discovery
  • Knowledge Discovery and Reasoning in Geospatial Applications
  • Data Mining and Discovery of Chemical Knowledge
  • Data Mining and Discovery of Astronomical Knowledge
  • Future Trends
  • On-board Data Mining
  • Data Streams: An Overview and Scientific Applications.

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