Übersicht			Auf mobile öffnen

Lieferstatus:	i.d.R. innert 7-14 Tagen versandfertig
Veröffentlichung:	Februar 2012
Genre:	EDV / Informatik
	computer science / COMPUTERS / Optical Data Processing / machine learning / pattern recognition
ISBN:	9780521190176
EAN-Code:	9780521190176
Verlag:	Cambridge Academic
Einband:	Gebunden
Sprache:	English
Dimensionen:	H 234 mm / B 157 mm / D 23 mm
Gewicht:	600 gr
Illustration:	79 b/w illus. 18 tables, Zeichnungen, schwarz-weiss, Raster,schwarz-weiss, Raster, nicht spezifiziert, Tabellen, nicht spezifiziert
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting, as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric convergence analysis and numerical stability analysis to complete the first and definitive treatment of the entire framework of density ratio estimation in machine learning.