Principles of Data Mining

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Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas. This book explains and explores the principal techniques of Data Mining: for classification, generation of association rules and...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Bramer, Max (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Springer London : Imprint: Springer, 2007.
Edición:1st ed. 2007.
Colección:Undergraduate Topics in Computer Science,
Temas:
Data structures (Computer science).
Information theory.
Computer science.
Information storage and retrieval systems.
Database management.
Artificial intelligence.
Computer programming.
Data Structures and Information Theory.
Theory of Computation.
Information Storage and Retrieval.
Database Management.
Artificial Intelligence.
Programming Techniques.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Data for Data Mining
  • to Classification: Na¨ive Bayes and Nearest Neighbour
  • Using Decision Trees for Classification
  • Decision Tree Induction: Using Entropy for Attribute Selection
  • Decision Tree Induction: Using Frequency Tables for Attribute Selection
  • Estimating the Predictive Accuracy of a Classifier
  • Continuous Attributes
  • Avoiding Overfitting of Decision Trees
  • More About Entropy
  • Inducing Modular Rules for Classification
  • Measuring the Performance of a Classifier
  • Association Rule Mining I
  • Association Rule Mining II
  • Clustering
  • Text Mining.

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