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Cluster Analysis For Data Mining And System Identification
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Book Synopsis Cluster Analysis for Data Mining and System Identification by : János Abonyi
Download or read book Cluster Analysis for Data Mining and System Identification written by János Abonyi and published by Springer Science & Business Media. This book was released on 2007-08-10 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to illustrate that advanced fuzzy clustering algorithms can be used not only for partitioning of the data. It can also be used for visualization, regression, classification and time-series analysis, hence fuzzy cluster analysis is a good approach to solve complex data mining and system identification problems. This book is oriented to undergraduate and postgraduate and is well suited for teaching purposes.
Book Synopsis Cluster Analysis for Data Mining and System Identification by : János Abonyi
Download or read book Cluster Analysis for Data Mining and System Identification written by János Abonyi and published by Springer Science & Business Media. This book was released on 2007-06-22 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to illustrate that advanced fuzzy clustering algorithms can be used not only for partitioning of the data. It can also be used for visualization, regression, classification and time-series analysis, hence fuzzy cluster analysis is a good approach to solve complex data mining and system identification problems. This book is oriented to undergraduate and postgraduate and is well suited for teaching purposes.
Download or read book Data Mining written by Krzysztof J. Cios and published by Springer Science & Business Media. This book was released on 2007-10-05 with total page 601 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive textbook on data mining details the unique steps of the knowledge discovery process that prescribes the sequence in which data mining projects should be performed, from problem and data understanding through data preprocessing to deployment of the results. This knowledge discovery approach is what distinguishes Data Mining from other texts in this area. The book provides a suite of exercises and includes links to instructional presentations. Furthermore, it contains appendices of relevant mathematical material.
Book Synopsis Descriptive Data Mining by : David L. Olson
Download or read book Descriptive Data Mining written by David L. Olson and published by Springer. This book was released on 2019-05-06 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of data mining methods demonstrated by software. Knowledge management involves application of human knowledge (epistemology) with the technological advances of our current society (computer systems) and big data, both in terms of collecting data and in analyzing it. We see three types of analytic tools. Descriptive analytics focus on reports of what has happened. Predictive analytics extend statistical and/or artificial intelligence to provide forecasting capability. It also includes classification modeling. Diagnostic analytics can apply analysis to sensor input to direct control systems automatically. Prescriptive analytics applies quantitative models to optimize systems, or at least to identify improved systems. Data mining includes descriptive and predictive modeling. Operations research includes all three. This book focuses on descriptive analytics. The book seeks to provide simple explanations and demonstration of some descriptive tools. This second edition provides more examples of big data impact, updates the content on visualization, clarifies some points, and expands coverage of association rules and cluster analysis. Chapter 1 gives an overview in the context of knowledge management. Chapter 2 discusses some basic software support to data visualization. Chapter 3 covers fundamentals of market basket analysis, and Chapter 4 provides demonstration of RFM modeling, a basic marketing data mining tool. Chapter 5 demonstrates association rule mining. Chapter 6 is a more in-depth coverage of cluster analysis. Chapter 7 discusses link analysis. Models are demonstrated using business related data. The style of the book is intended to be descriptive, seeking to explain how methods work, with some citations, but without deep scholarly reference. The data sets and software are all selected for widespread availability and access by any reader with computer links.
Book Synopsis Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection by : Koyuncugil, Ali Serhan
Download or read book Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection written by Koyuncugil, Ali Serhan and published by IGI Global. This book was released on 2010-09-30 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection has never been more important, as the research this book presents an alternative to conventional surveillance and risk assessment. This book is a multidisciplinary excursion comprised of data mining, early warning systems, information technologies and risk management and explores the intersection of these components in problematic domains. It offers the ability to apply the most modern techniques to age old problems allowing for increased effectiveness in the response to future, eminent, and present risk.
Book Synopsis Handbook of Statistical Analysis and Data Mining Applications by : Ken Yale
Download or read book Handbook of Statistical Analysis and Data Mining Applications written by Ken Yale and published by Elsevier. This book was released on 2017-11-09 with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. - Includes input by practitioners for practitioners - Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models - Contains practical advice from successful real-world implementations - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions - Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
Book Synopsis Handbook of Cluster Analysis by : Christian Hennig
Download or read book Handbook of Cluster Analysis written by Christian Hennig and published by CRC Press. This book was released on 2015-12-16 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Cluster Analysis provides a comprehensive and unified account of the main research developments in cluster analysis. Written by active, distinguished researchers in this area, the book helps readers make informed choices of the most suitable clustering approach for their problem and make better use of existing cluster analysis tools.The
Book Synopsis Rough Sets, Fuzzy Sets, Data Mining and Granular Computing by : Hiroshi Sakai
Download or read book Rough Sets, Fuzzy Sets, Data Mining and Granular Computing written by Hiroshi Sakai and published by Springer Science & Business Media. This book was released on 2009-11-30 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2009), held at the Indian Institute of Technology (IIT), Delhi, India, during December 15-18, 2009. RSFDGrC is a series of conferences spanning over the last 15 years. It investigates the me- ing points among the four major areas outlined in its title. This year, it was co-organized with the Third International Conference on Pattern Recognition and Machine Intelligence (PReMI 2009), which provided additional means for multi-facetedinteractionofboth scientists andpractitioners.Itwasalsothe core component of this year's Rough Set Year in India project. However, it remained a fully international event aimed at building bridges between countries. The ?rst sectin contains the invited papers and a short report on the abo- mentioned project. Let us note that all the RSFDGrC 2009 plenary speakers, Ivo Düntsch, Zbigniew Suraj, Zhongzhi Shi, Sergei Kuznetsov, Qiang Shen, and Yukio Ohsawa, contributed with the full-length articles in the proceedings. The remaining six sections contain 56 regular papers that were selected out of 130 submissions, each peer-reviewed by three PC members. We thank the authors for their high-quality papers submitted to this volume and regret that many deserving papers could not be accepted because of our urge to maintain strict standards. It is worth mentioning that there was quite a good number of papers on the foundations of rough sets and fuzzy sets, many of them authored byIndianresearchers.ThefuzzysettheoryhasbeenpopularinIndiaforalonger time. Now, we can see the rising interest in the rough set theory.
Book Synopsis Intelligent Systems in Production Engineering and Maintenance by : Anna Burduk
Download or read book Intelligent Systems in Production Engineering and Maintenance written by Anna Burduk and published by Springer. This book was released on 2018-07-31 with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book presents a collection of 103 peer-reviewed articles from the Second International Conference on Intelligent Systems in Production Engineering and Maintenance (ISPEM 2018). The conference was organized by the Faculty of Mechanical Engineering and CAMT (Centre for Advanced Manufacturing Technologies), Wrocław University of Science and Technology and was held in Wrocław (Poland) on 17–18 September 2018. The conferences topics included the possibility of using a wide range of intelligent methods in production engineering, presenting and discussing new solutions for innovative plants, research findings and case studies demonstrating advances in production and maintenance from the point of view of Industry 4.0 – particularly applications of intelligent systems, methods and tools in production engineering, maintenance, logistics, quality management, information systems and product development. The book is divided into two parts: the first includes papers related to intelligent systems in production engineering, while the second is dedicated to special sessions focusing on: 1. Computer Aided methods in Production Engineering 2. Mining 4.0 and Intelligent Mining Transportation 3. Modelling and Simulation of Production Processes 4. Multi-Faceted Modelling of Networks and Processes 5. Product Design and Product Manufacturing in Industry 4.0 This book is an excellent source of information for scientists in the field of manufacturing engineering and for top managers in production enterprises.
Book Synopsis Intelligent Data Analysis and Applications by : Ajith Abraham
Download or read book Intelligent Data Analysis and Applications written by Ajith Abraham and published by Springer. This book was released on 2015-07-14 with total page 543 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume of Advances in Intelligent Systems and Computing contains accepted papers presented in the main track of ECC 2015, the Second Euro-China Conference on Intelligent Data Analysis and Applications. The aim of ECC is to provide an internationally respected forum for scientific research in the broad area of intelligent data analysis, computational intelligence, signal processing, and all associated applications of AIs. The second edition of ECC was organized jointly by VSB - Technical University of Ostrava, Czech Republic, and Fujian University of Technology, Fuzhou, China. The conference, organized under the patronage of Mr. Miroslav Novak, President of the Moravian-Silesian Region, took place in late June and early July 2015 in the Campus of the VSB - Technical University of Ostrava, Czech Republic.
Book Synopsis Advances in Spatio-Temporal Segmentation of Visual Data by : Vladimir Mashtalir
Download or read book Advances in Spatio-Temporal Segmentation of Visual Data written by Vladimir Mashtalir and published by Springer Nature. This book was released on 2019-12-16 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes a number of promising models and methods for adaptive segmentation, swarm partition, permissible segmentation, and transform properties, as well as techniques for spatio-temporal video segmentation and interpretation, online fuzzy clustering of data streams, and fuzzy systems for information retrieval. The main focus is on the spatio-temporal segmentation of visual information. Sets of meaningful and manageable image or video parts, defined by visual interest or attention to higher-level semantic issues, are often vital to the efficient and effective processing and interpretation of viewable information. Developing robust methods for spatial and temporal partition represents a key challenge in computer vision and computational intelligence as a whole. This book is intended for students and researchers in the fields of machine learning and artificial intelligence, especially those whose work involves image processing and recognition, video parsing, and content-based image/video retrieval.
Download or read book Data Clustering written by and published by BoD – Books on Demand. This book was released on 2022-08-17 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: In view of the considerable applications of data clustering techniques in various fields, such as engineering, artificial intelligence, machine learning, clinical medicine, biology, ecology, disease diagnosis, and business marketing, many data clustering algorithms and methods have been developed to deal with complicated data. These techniques include supervised learning methods and unsupervised learning methods such as density-based clustering, K-means clustering, and K-nearest neighbor clustering. This book reviews recently developed data clustering techniques and algorithms and discusses the development of data clustering, including measures of similarity or dissimilarity for data clustering, data clustering algorithms, assessment of clustering algorithms, and data clustering methods recently developed for insurance, psychology, pattern recognition, and survey data.
Book Synopsis Encyclopedia of Data Warehousing and Mining by : Wang, John
Download or read book Encyclopedia of Data Warehousing and Mining written by Wang, John and published by IGI Global. This book was released on 2005-06-30 with total page 1382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Warehousing and Mining (DWM) is the science of managing and analyzing large datasets and discovering novel patterns and in recent years has emerged as a particularly exciting and industrially relevant area of research. Prodigious amounts of data are now being generated in domains as diverse as market research, functional genomics and pharmaceuticals; intelligently analyzing these data, with the aim of answering crucial questions and helping make informed decisions, is the challenge that lies ahead. The Encyclopedia of Data Warehousing and Mining provides a comprehensive, critical and descriptive examination of concepts, issues, trends, and challenges in this rapidly expanding field of data warehousing and mining (DWM). This encyclopedia consists of more than 350 contributors from 32 countries, 1,800 terms and definitions, and more than 4,400 references. This authoritative publication offers in-depth coverage of evolutions, theories, methodologies, functionalities, and applications of DWM in such interdisciplinary industries as healthcare informatics, artificial intelligence, financial modeling, and applied statistics, making it a single source of knowledge and latest discoveries in the field of DWM.
Book Synopsis Encyclopedia of Information Science and Technology, Third Edition by : Khosrow-Pour, Mehdi
Download or read book Encyclopedia of Information Science and Technology, Third Edition written by Khosrow-Pour, Mehdi and published by IGI Global. This book was released on 2014-07-31 with total page 7972 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This 10-volume compilation of authoritative, research-based articles contributed by thousands of researchers and experts from all over the world emphasized modern issues and the presentation of potential opportunities, prospective solutions, and future directions in the field of information science and technology"--Provided by publisher.
Book Synopsis Data Clustering: Theory, Algorithms, and Applications, Second Edition by : Guojun Gan
Download or read book Data Clustering: Theory, Algorithms, and Applications, Second Edition written by Guojun Gan and published by SIAM. This book was released on 2020-11-10 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.
Book Synopsis Encyclopedia of Information Science and Technology by : Mehdi Khosrow-Pour
Download or read book Encyclopedia of Information Science and Technology written by Mehdi Khosrow-Pour and published by IGI Global Snippet. This book was released on 2009 with total page 4292 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This set of books represents a detailed compendium of authoritative, research-based entries that define the contemporary state of knowledge on technology"--Provided by publisher.
Book Synopsis Principles of Data Mining by : David J. Hand
Download or read book Principles of Data Mining written by David J. Hand and published by MIT Press. This book was released on 2001-08-17 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.
