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Author: Zhenyuan Wang
Publisher: World Scientific
ISBN: 9812814671
Category : Computers
Languages : en
Pages : 359
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Book Description
Regarding the set of all feature attributes in a given database as the universal set, this monograph discusses various nonadditive set functions that describe the interaction among the contributions from feature attributes towards a considered target attribute. Then, the relevant nonlinear integrals are investigated. These integrals can be applied as aggregation tools in information fusion and data mining, such as synthetic evaluation, nonlinear multiregressions, and nonlinear classifications. Some methods of fuzzification are also introduced for nonlinear integrals such that fuzzy data can be treated and fuzzy information is retrievable. The book is suitable as a text for graduate courses in mathematics, computer science, and information science. It is also useful to researchers in the relevant area.
Author: Zhenyuan Wang
Publisher: World Scientific
ISBN: 9812814671
Category : Computers
Languages : en
Pages : 359
Get Book Here
Book Description
Regarding the set of all feature attributes in a given database as the universal set, this monograph discusses various nonadditive set functions that describe the interaction among the contributions from feature attributes towards a considered target attribute. Then, the relevant nonlinear integrals are investigated. These integrals can be applied as aggregation tools in information fusion and data mining, such as synthetic evaluation, nonlinear multiregressions, and nonlinear classifications. Some methods of fuzzification are also introduced for nonlinear integrals such that fuzzy data can be treated and fuzzy information is retrievable. The book is suitable as a text for graduate courses in mathematics, computer science, and information science. It is also useful to researchers in the relevant area.
Author: Zhenyuan Wang
Publisher: World Scientific
ISBN: 981281468X
Category : Computers
Languages : en
Pages : 359
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Book Description
Ch. 1. Introduction -- ch. 2. Basic knowledge on classical sets. 2.1. Classical sets and set inclusion. 2.2. Set operations. 2.3. Set sequences and set classes. 2.4. Set classes closed under set operations. 2.5. Relations, posets, and lattices. 2.6. The supremum and infimum of real number sets -- ch. 3. Fuzzy sets. 3.1. The membership functions of fuzzy sets. 3.2. Inclusion and operations of fuzzy sets. 3.3. [symbol]-cuts. 3.4. Convex fuzzy sets. 3.5. Decomposition theorems. 3.6. The extension principle. 3.7. Interval numbers. 3.8. Fuzzy numbers and linguistic attribute. 3.9. Binary operations for fuzzy numbers. 3.10. Fuzzy integers -- ch. 4. Set functions. 4.1. Weights and classical measures. 4.2. Extension of measures. 4.3. Monotone measures. 4.4. [symbol]-measures. 4.5. Quasi-measures. 4.6. Mobius and zeta transformations. 4.7. Belief measures and plausibility measures. 4.8. Necessity measures and possibility measures. 4.9. k-interactive measures. 4.10. Efficiency measures and signed efficiency measures -- ch. 5. Integrations. 5.1. Measurable functions. 5.2. The Riemann integral. 5.3. The Lebesgue-Like integral. 5.4. The Choquet integral. 5.5. Upper and lower integrals. 5.6. r-integrals on finite spaces -- ch. 6. Information fusion. 6.1. Information sources and observations. 6.2. Integrals used as aggregation tools. 6.3. Uncertainty associated with set functions. 6.4. The inverse problem of information fusion -- ch. 7. Optimization and soft computing. 7.1. Basic concepts of optimization. 7.2. Genetic algorithms. 7.3. Pseudo gradient search. 7.4. A hybrid search method -- ch. 8. Identification of set functions. 8.1. Identification of [symbol]-measures. 8.2. Identification of belief measures. 8.3. Identification of monotone measures. 8.4. Identification of signed efficiency measures by a genetic algorithm. 8.5. Identification of signed efficiency measures by the pseudo gradient. 8.6. Identification of signed efficiency measures based on the Choquet integral by an algebraic method. 8.7. Identification of monotone measures based on r-integrals by a genetic algorithm -- ch. 9. Multiregression based on nonlinear integrals. 9.1. Linear multiregression. 9.2. Nonlinear multiregression based on the Choquet integral. 9.3. A nonlinear multiregression model accommodating both categorical and numerical predictive attributes. 9.4. Advanced consideration on the multiregression involving nonlinear integrals -- ch. 10. Classifications based on nonlinear integrals. 10.1. Classification by an integral projection. 10.2. Nonlinear classification by weighted Choquet integrals. 10.3. An example of nonlinear classification in a three-dimensional sample space. 10.4. The uniqueness problem of the classification by the Choquet integral with a linear core. 10.5. Advanced consideration on the nonlinear classification involving the Choquet integral -- ch. 11. Data mining with fuzzy data. 11.1. Defuzzified Choquet Integral with Fuzzy-Valued Integrand (DCIFI). 11.2. Classification model based on the DCIFI. 11.3. Fuzzified Choquet Integral with Fuzzy-Valued Integrand (FCIFI). 11.4. Regression model based on the CIII
Author: Yong Shi
Publisher: Springer Science & Business Media
ISBN: 0857295047
Category : Computers
Languages : en
Pages : 314
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Book Description
Optimization techniques have been widely adopted to implement various data mining algorithms. In addition to well-known Support Vector Machines (SVMs) (which are based on quadratic programming), different versions of Multiple Criteria Programming (MCP) have been extensively used in data separations. Since optimization based data mining methods differ from statistics, decision tree induction, and neural networks, their theoretical inspiration has attracted many researchers who are interested in algorithm development of data mining. Optimization based Data Mining: Theory and Applications, mainly focuses on MCP and SVM especially their recent theoretical progress and real-life applications in various fields. These include finance, web services, bio-informatics and petroleum engineering, which has triggered the interest of practitioners who look for new methods to improve the results of data mining for knowledge discovery. Most of the material in this book is directly from the research and application activities that the authors’ research group has conducted over the last ten years. Aimed at practitioners and graduates who have a fundamental knowledge in data mining, it demonstrates the basic concepts and foundations on how to use optimization techniques to deal with data mining problems.
Author: Suresh Chandra Satapathy
Publisher: Springer Science & Business Media
ISBN: 3319030957
Category : Technology & Engineering
Languages : en
Pages : 780
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Book Description
This volume contains 85 papers presented at CSI 2013: 48th Annual Convention of Computer Society of India with the theme “ICT and Critical Infrastructure”. The convention was held during 13th –15th December 2013 at Hotel Novotel Varun Beach, Visakhapatnam and hosted by Computer Society of India, Vishakhapatnam Chapter in association with Vishakhapatnam Steel Plant, the flagship company of RINL, India. This volume contains papers mainly focused on Data Mining, Data Engineering and Image Processing, Software Engineering and Bio-Informatics, Network Security, Digital Forensics and Cyber Crime, Internet and Multimedia Applications and E-Governance Applications.
Author:
Publisher:
ISBN:
Category : Fuzzy arithmetic
Languages : en
Pages : 548
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Book Description
Author: Hakikur Rahman
Publisher: IGI Global Snippet
ISBN:
Category : Business & Economics
Languages : en
Pages : 368
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Book Description
"This book presents an overview on the main issues of data mining, including its classification, regression, clustering, and ethical issues"--Provided by publisher.
Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 994
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Book Description
Author: Petra Perner
Publisher: Springer
ISBN: 3540707204
Category : Computers
Languages : en
Pages : 454
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Book Description
ICDM / MLDM Medaillie (limited edition) Meissner Porcellan, the “White Gold” of King August the Strongest of Saxonia ICDM 2008 was the eighth event of the Industrial Conference on Data Mining held in Leipzig (www.data-mining-forum.de). For this edition the Program Committee received 116 submissions from 20 countries. After the peer-review process, we accepted 36 high-quality papers for oral presentation, which are included in these proceedings. The topics range from aspects of classification and prediction, clustering, Web mining, data mining in medicine, applications of data mining, time series and frequent pattern mining, and association rule mining. Thirteen papers were selected for poster presentations that are published in the ICDM Poster Proceeding Volume. In conjunction with ICDM there were three workshops focusing on special hot application-oriented topics in data mining. The workshop Data Mining in Life Science DMLS 2008 was held the third time this year and the workshop Data Mining in Marketing DMM 2008 ran for the second time this year. Additionally, we introduced an International Workshop on Case-Based Reasoning for Multimedia Data CBR-MD.
Author: Cengiz Kahraman
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 640
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Book Description
After an introductory chapter explaining recent applications of fuzzy sets in IE, this book explores the seven major areas of IE to which fuzzy set theory can contribute: Control and Reliability, Engineering Economics and Investment Analysis, Group and Multi-criteria Decision-making, Human Factors Engineering and Ergonomics, Manufacturing Systems and Technology Management, Optimization Techniques, and Statistical Decision-making. Under these major areas, every chapter includes didactic numerical applications.
Author: V. Lakshmikantham
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 728
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Book Description
Nonlinear Systems and Applications ...
