【ZDW】Learning from Data: Concepts, Theory, and Methods_Cherkassky, Vl

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[商品主貨號] U103011618

[ISBN-13碼] 9780471681823

[ISBN] 0471681822

[作者] Cherkassky, Vladimir/ Mulier, Filip M.

[出版社] Wiley-IEEE Press

[出版日期] 2007/08/24

[裝訂/規格] 精裝 / 538頁 / 23.4 x 16.5 x 3.3 cm / 普通級 / 再版

[內容簡介] (出版商制式文字, 不論標題或內容簡介是否有標示, 請都以『沒有附件、沒有贈品』為參考。)

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. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.

Vladimir CherKassky, PhD, is Professor of Electrical and Computer Engineering at the University of Minnesota. He is internationally known for his research on neural networks and statistical learning.

Filip Mulier, PhD, has worked in the software field for the last twelve years, part of which has been spent researching, developing, and applying advanced statistical and machine learning methods. He currently holds a project management position.)

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