Learning from Data
Cherkassky, Vladimir / Mulier, Filip M
An interdisciplinary framework for learning methodologies-now revised and updated
Learning from Data 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 pattern recognition can be applied-showing that a few fundamental principles underlie most new methods being proposed today in stat...