Learning from data : Concepts, theory, and methods
Cherkassky, Vladimir S.
Learning from data : Concepts, theory, and methods by Vladimir Cherkassky and Filip Mulier - 2nd ed 2007 - 1 recurso en línea
Incluye índice y referencias bibliográficas (páginas 519-531)
Problem statement, classical approaches, and adaptive learning -- Regularization framework -- Statistical learning theory -- Nonlinear optimization strategies -- Methods for data reduction and dimensionality reduction -- Methods for regression -- Classification -- Support vector machines -- Noninductive inference and alternative learning formulations
An interdisciplinary framework for learning methodologies--covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied--showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science
9780470140529 9780470140512
10.1002/9780470140529 doi
Ingeniería del software
TK5102.9 / 2007 EB
Learning from data : Concepts, theory, and methods by Vladimir Cherkassky and Filip Mulier - 2nd ed 2007 - 1 recurso en línea
Incluye índice y referencias bibliográficas (páginas 519-531)
Problem statement, classical approaches, and adaptive learning -- Regularization framework -- Statistical learning theory -- Nonlinear optimization strategies -- Methods for data reduction and dimensionality reduction -- Methods for regression -- Classification -- Support vector machines -- Noninductive inference and alternative learning formulations
An interdisciplinary framework for learning methodologies--covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied--showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science
9780470140529 9780470140512
10.1002/9780470140529 doi
Ingeniería del software
TK5102.9 / 2007 EB