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Thursday, May 14, 2020 | History

3 edition of Optimization based data mining found in the catalog.

Optimization based data mining

Yong Shi

Optimization based data mining

theory and applications

by Yong Shi

  • 247 Want to read
  • 14 Currently reading

Published by Springer-Verlag in London, New York .
Written in English

    Subjects:
  • Data mining

  • Edition Notes

    Includes bibliographic references (p. 295-305) and indexes. 254

    StatementYong Shi ... [et al]
    SeriesAdvanced information and knowledge processing, Advanced information and knowledge processing
    Classifications
    LC ClassificationsQA76.9.D343 S55 2011
    The Physical Object
    Paginationxv, 316 p. :
    Number of Pages316
    ID Numbers
    Open LibraryOL25166235M
    ISBN 100857295039
    ISBN 109780857295033
    LC Control Number2011929129
    OCLC/WorldCa706784632

    Find many great new & used options and get the best deals for Optimization Based Data Mining: Theory and Applications by Yong Shi (English) Pa at the best online prices at . Business intelligence: data mining and optimization for decision making / Carlo Vercellis. p. cm. Includes bibliographical references and index. ISBN (cloth) – ISBN (pbk.: alk. paper) 1. Decision making–Mathematical models. 2. Business intelligence. 3. Data mining. I. Title. HDV File Size: KB.

    Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures Meng P Tan, # 1 Erin N Smith, # 2 James R Broach, # 3 and Christodoulos A Floudas # 1 1 Department of Chemical Engineering, Princeton University, NJ, USACited by:   Business Intelligence provides coverage of a broad spectrum of topics currently dispersed throughout data mining and business books. In bringing these topics together for the first time the book provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence.

    HVAC SYSTEM MODELING AND OPTIMIZATION: A DATA-MINING APPROACH. by. Fan Tang. A thesis submitted in partial fulfillment. of the requirements for the Master of Science. degree in Industrial Engineering. in the Graduate College of. The University of Iowa. December Thesis Supervisor: Professor Andrew Kusiak. Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and transform the information into a comprehensible structure for.


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Optimization based data mining by Yong Shi Download PDF EPUB FB2

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 by: The Paperback of the Optimization Based Data Mining: Theory and Applications by Yong Shi, Yingjie Tian, Gang Kou, Yi Peng | at Barnes & Noble.

FREE Due to COVID, orders may be delayed. Yong Shi has 28 books on Goodreads with 19 ratings. Yong Shi’s most popular book is Optimization Based Data Mining: Theory and Applications. Optimization Based Data Mining Theory and Applications by Yong Shi, Yingjie Tian, Gang Kou.

Published by Springer. 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.

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 Optimization based data mining book who look for new methods to improve.

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. 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.

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 : Yong Shi, Yingjie Tian, Gang Kou.

Optimization of a Language for Data Mining. constraint-based data mining, emerging research topics lying at the intersection of data mining and database research. The book provides an overview Author: Rosa Meo.

The field of data mining increasingly adapts methods and algorithms from advanced matrix computations, graph theory and optimization. In these methods, the data is described using matrix representations (graphs are represented by their adjacency matrices) and the data mining problem is formulated as an optimization problem with matrix variables.

With these, the data mining task becomes a process of. Optimization techniques have been widely adopted to implement various data mining algorithms. This book focuses on cutting-edge theoretical developments and real-life applications in optimization, covering a range of fields from finance to bioinformatics.

The increasing volume of data in modern business and science calls for more complex and sophisticated tools. Although advances in data mining technology have made extensive data collection much easier, it's still always evolving and there is a constant need for new techniques and tools that can help us transform this data into useful information and knowledge.

Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series Book 29) - Kindle edition by Deng, Naiyang, Tian, Yingjie, Zhang, Chunhua.

Download it once and read it on your Kindle device, PC, phones or tablets. Use features like bookmarks, note taking and highlighting while reading Support Vector /5(2). Data Mining in Agriculture (Springer Optimization and Its Applications Book 34) Kindle Edition by Antonio Mucherino (Author), Petraq Papajorgji (Author), Panos M.

Pardalos (Author) PDF by Author on in Books, Data Mining. Biologically Inspired Techniques for Data Mining: A Brief Overview of Particle Swarm Optimization for KDD: /ch Knowledge Discovery and Data (KDD) mining helps uncover hidden knowledge in huge amounts of data.

However, recently, different researchers have questioned theCited by: 2. Data mining with various optimization methods. In this paper a novel approach for modelling traffic noise that is based on optimization is presented. Four optimization techniques were used in simulation in this work: genetic algorithms, Hooke and Jeeves algorithm, simulated annealing and particle swarm optimization.

Based on these data Cited by: The results presented are useful for researchers in combinatorial optimization, data mining, knowledge discovery, machine learning, and finite element methods, especially those working in rough set theory, test theory, logical analysis of data, and PDE solvers.

This book can. apply novel optimization-based data mining approaches to the study of brain physiology, which might be able to revolutionize current diagnosis and treatment of epilepsy.

Through quantitative analyses of electroencephalogram (EEG) recordings, a new data mining paradigm for feature selection and clustering is developed based on mathemat. Support Vector Machines Optimization Based Theory, Algorithms, and Extensions (Chapman & Hall-CRC Data Mining and Knowle. Analysis of Gravitation-Based Optimization Algorithms for Clustering and Classification: /ch In recent years, various heuristic algorithms based on natural phenomena and swarm behaviors were introduced to solve innumerable optimization problems.

TheseCited by: 1.An automated three-dimensional multi-objective optimization and data mining method is presented by integrating a self-adaptive multi-objective differential evolution algorithm (SMODE), 3D parameterization method for blade profile and meridional channel, Reynolds-averaged Navier–Stokes (RANS) solver technique and data mining technique of self-organizing map (SOM).Cited by: Optimization Of A Power Plant By Using Data Mining And Its Techniques 83 OPTIMIZATION OF A POWER PLANT BY USING DATA MINING AND ITS TECHNIQUES 1HIMANI TYAGI, 2RAJAT KUMAR -CSE(Ideal Institute of Technology), IT (ABES Engineering College) Ghaziabad, India (Power), National Power Training institute Delhi, India.