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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Kubat, Miroslav (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2015.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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.