中图分类法:	TP181 版次：
著者:	Theodoridis, Sergios,
题名:	Machine learning : [ a Bayesian and optimization perspective /] / ,
出版发行:	出版地： London, UK : 出版社： Academic Press is an imprint of Elsevier, 出版日期： [2015]
载体形态:	xxi, 1050 p. : ill. ; 26 cm.
载体形态:	1 online resource : illustrations
内容提要:	This book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth. Topics include: all major classical techniques: mean/least-squares regression and filtering, Kalman filtering, stochastic approximation and online learning, Bayesian classification, decision trees, logistic regression and boosting methods; latest trends; case studies - protein folding prediction, optical character recognition, text authorship identification, fMRI data analysis, change point detection, hyperspectral image unmixing, target localization, channel equalization and echo cancellation, and how the theory can be applied. --
主题词:	Machine learning.
主题词:	Mathematical optimization.
主题词:	Bayesian statistical decision theory.
索书号:	1