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lio Nazionale delle Ricerche, Rome, Italy  \nCarlo Vercellis  \nPolitec nico di Milano, Italy  \nInformatIon scIence reference  \nHershey • New York  \nAcquisitions Editor: Kristin Klinger  \nDevelopment Editor: Kristin Roth  \nSenior Managing Editor: Jennifer Neidig  \nManaging Editor: Sara Reed  \nCopy Editor: Angela Thor  \nTypesetter: Jamie Snavely  \nCover Design: Lisa Tosheff  \nPrinted at: Yurchak Printing Inc.  \nPublished in the United States of America by  \nInformation Science Reference (an imprint ofIGI Global)  \n701 E. Chocolate Avenue, Suite 200  \nHershey PA 17033  \nTel: 717-533-8845  \nFax: 717-533-8661  \nE-mail: [cust@igi-global.com](cust@igi-global.com)  \nWeb site: [http://www.igi-global.com/reference](http://www.igi-global.com/reference)  \nand in the United Kingdom by  \nInformation Science Reference (an imprint ofIGI Global)  \n3 Henrietta Street  \nCovent Garden  \nLondon WC2E 8LU  \nTel: 44 20 7240 0856  \nFax: 44 20 7379 0609  \nWeb site: [http://www.eurospanonline.com](http://www.eurospanonline.com)  \nCopyright © 2008 by IGI Global. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher.  \nProduct or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark.  \nLibrary of Congress Cataloging-in-Publication Data Felici, Giovanni.  \nMathematical methods for knowledge discovery and data mining / Giovanni Felici & Carlo Vercellis, editors.  \n[p. cm](p. cm).  \nSummary: “This book focuses on the mathematical models and methods that support most data mining applications and solution techniques, covering such topics as association rules; Bayesian methods; data visualization; kernel methods; neural networks; text, speech, and image recognition; an invaluable resource for scholars and practitioners in the fields of biomedicine, engineering, finance, manufacturing, marketing, performance measurement, and telecommunications”--Provided by publisher.  \nIncludes bibliographical references and index.  \nISBN 978-1-59904-528-3 (hardcover) --ISBN 978-1-59904-530-6 (ebook)  \n1. Data mining. 2. Data mining--Mathematical models. 3. Knowledge acquisition (Expert systems) I. Felici, Giovanni. II. Vercellis, Carlo. III. Title.  \nQA76 .9.D343F46 2007 006.3’12--dc22  \n2007022228  \nBritish Cataloguing in Publication Data  \nA Cataloguing in Publication record for this book is available from the British Library.  \nAll work contributed to this book set is new, previously-unpublished material. The views expressed in this book are those of the authors, but not necessarily of the publisher.  \nTable of Contents  \nForeword ............................................................................................................................................. xii  \nPreface ................................................................................................................................................ xiv  \nAcknowledgment ................................................................................................................................ xx  \nChapter I  \nDiscretization of Rational Data / Jonathan Mugan and Klaus Truemper .............................................. 1  \nChapter II  \nVector DNF for Datasets Classifications: Application to the Financial Timing Decision Problem / Massimo Liquori and Andrea Scozzari ................................................................. 24  \nChapter III  \nReducing a Class of Machine Learning Algorithms to Logical Commonsense Reasoning Operations / Xenia Naidenova ........................................................................................... 41  \nChapter IV  \nThe Analysis of Service Q","cbCaiubBbqbDFDXA","https://ap.wps.com/l/cbCaiubBbqbDFDXA","pdf",6030436,394,"English","# Foreword\n# Preface\n# Acknowledgment\n# Discretization of Rational Data\n# Vector DNF for Datasets Classifications: Application to the Financial Timing Decision Problem\n# Reducing a Class of Machine Learning Algorithms to Logical Commonsense Reasoning Operations\n# The Analysis of Service Quality Through Stated Preference Models and Rule-Based Classification\n# Support Vector Machines for Business Applications\n# Kernel Width Selection for SVM Classification: A Meta-Learning Approach\n# Protein Folding Classification Through Multicategory Discrete SVM\n# Hierarchical Profiling, Scoring, and Applications in Bioinformatics\n# Hierarchical Clustering Using Evolutionary Algorithms\n# Exploratory Time Series Data Mining by Genetic Clustering\n# Development of Control Signatures with a Hybrid Data Mining and Genetic Algorithm\n# Bayesian Belief Networks for Data Cleaning\n# A Comparison of Revision Schemes for Cleaning Labeling Noise\n# Improving Web Clickstream Analysis: Markov Chains Models and Genmax Algorithms","[{\"question\":\"What is the book focused on?\",\"answer\":\"It focuses on mathematical models and methods that support data mining applications and solution techniques across many problem domains.\"},{\"question\":\"Which data mining topics are covered?\",\"answer\":\"Topics include association rules, Bayesian methods, data visualization, kernel methods, neural networks, and recognition methods for text, speech, and images.\"},{\"question\":\"What kinds of references and navigation tools are included?\",\"answer\":\"The book includes bibliographical references and an index, and it provides a detailed table of contents listing the chapters and their topics.\"}]","Mathematical Methods for Knowledge Discovery and Data Mining | PDF",1789974847,993]