02002cam a22003015a 4500 ssj0001558340 OSt 20201128023735.0 150715t2015 gw a frb 001 0 eng d 9783319200095 WaSeSS EG-ScBUE eng 006.3 22 KUB Kubat, Miroslav, 39937 1958- An Introduction to Machine Learning / Miroslav Kubat. Cham : Springer, c.2015. xiii, 291 p. : ill. ; 24 cm. Index : p. 291. Bibliography : p. 287-290. 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. Available on campus and off campus with authorized login. 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, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to combine these simple tools by way of “boosting, ” how to exploit them in more complicated domains, and how to deal with diverse advanced practical issues. One chapter is dedicated to the popular genetic algorithms. Machine learning. BUEsh 2922 COMSCI May2016 SpringerLink (Online service) Springer eBooks Printed edition: 9783319200095 ddc 21712 21684 0 0 ddc 0 0 Alahram MAIN MAIN LOW 2016-05-09 Purchase 450.00 3 34 006.3 KUB 000032448 2025-07-15 00:00:00 2018-10-01 562.50 BB