An Introduction to Machine Learning

This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, lin...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Kubat, Miroslav (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Temas:
Artificial intelligence.
Computer simulation.
Information storage and retrieval systems.
Pattern recognition systems.
Artificial Intelligence.
Computer Modelling.
Information Storage and Retrieval.
Automated Pattern Recognition.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • A Simple Machine-Learning Task
  • Probabilities: Bayesian Classifiers
  • Similarities: Nearest-Neighbor Classifiers
  • Inter-Class Boundaries: Linear and Polynomial Classifiers
  • Artificial Neural Networks
  • Decision Trees
  • Computational Learning Theory
  • A Few Instructive Applications
  • Induction of Voting Assemblies
  • Some Practical Aspects to Know About
  • Performance Evaluation.-Statistical Significance
  • The Genetic Algorithm
  • Reinforcement learning.

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