Data Mining Methods For Knowledge Discovery PDF Download
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Author | : Krzysztof J. Cios |
Publisher | : Springer Science & Business Media |
Total Pages | : 508 |
Release | : 2012-12-06 |
Genre | : Computers |
ISBN | : 1461555892 |
Download Data Mining Methods for Knowledge Discovery Book in PDF, ePub and Kindle
Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently used in the process of knowledge discovery. This book first elaborates on the fundamentals of each of the data mining methods: rough sets, Bayesian analysis, fuzzy sets, genetic algorithms, machine learning, neural networks, and preprocessing techniques. The book then goes on to thoroughly discuss these methods in the setting of the overall process of knowledge discovery. Numerous illustrative examples and experimental findings are also included. Each chapter comes with an extensive bibliography. Data Mining Methods for Knowledge Discovery is intended for senior undergraduate and graduate students, as well as a broad audience of professionals in computer and information sciences, medical informatics, and business information systems.
Author | : Krzysztof J. Cios |
Publisher | : Springer Science & Business Media |
Total Pages | : 601 |
Release | : 2007-10-05 |
Genre | : Computers |
ISBN | : 0387367950 |
Download Data Mining Book in PDF, ePub and Kindle
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.
Author | : O. Maimon |
Publisher | : Springer Science & Business Media |
Total Pages | : 192 |
Release | : 2000-12-31 |
Genre | : Computers |
ISBN | : 9780792366478 |
Download Knowledge Discovery and Data Mining Book in PDF, ePub and Kindle
This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http://www.eng.tau.ac.iV-maimonlifn-kdg£). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results).
Author | : Joao Gama |
Publisher | : CRC Press |
Total Pages | : 256 |
Release | : 2010-05-25 |
Genre | : Business & Economics |
ISBN | : 1439826129 |
Download Knowledge Discovery from Data Streams Book in PDF, ePub and Kindle
Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents
Author | : Alex A. Freitas |
Publisher | : Springer Science & Business Media |
Total Pages | : 272 |
Release | : 2013-11-11 |
Genre | : Computers |
ISBN | : 3662049236 |
Download Data Mining and Knowledge Discovery with Evolutionary Algorithms Book in PDF, ePub and Kindle
This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics
Author | : A. H. Eschenfelder |
Publisher | : Springer Science & Business Media |
Total Pages | : 328 |
Release | : 2012-12-06 |
Genre | : Technology & Engineering |
ISBN | : 3642965490 |
Download Magnetic Bubble Technology Book in PDF, ePub and Kindle
Magnetic bubbles are of interest to engineers because their properties can be used for important practical electronic devices and they are of interest to physicists because their properties are manifestations of intriguing physical principles. At the same time, the fabrication of useful configurations challenges the materials scientists and engineers. A technology of magnetic bubbles has developed to the point where commercial products are being marketed. In addition, new discovery and development are driving this technology toward substantially lower costs and presumably broader application. For all of these reasons there is a need to educate newcomers to this field in universities and in industry. The purpose of this book is to provide a text for a one-semester course that can be taught under headings of Solid State Physics, Materials Science, Computer Technology or Integrated Electronics. It is expected that the student of anyone of these disciplines will be interested in each of the chapters of this book to some degree, but may concentrate on some more than others, depending on the discipline. At the end of each chapter there is a brief summary which will serve as a reminder of the contents of the chapter but can also be read ahead of time to determine the depth of your interest in the chapter.
Author | : Oded Maimon |
Publisher | : Springer Science & Business Media |
Total Pages | : 1269 |
Release | : 2010-09-10 |
Genre | : Computers |
ISBN | : 0387098232 |
Download Data Mining and Knowledge Discovery Handbook Book in PDF, ePub and Kindle
This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.
Author | : Felici, Giovanni |
Publisher | : IGI Global |
Total Pages | : 394 |
Release | : 2007-10-31 |
Genre | : Computers |
ISBN | : 1599045303 |
Download Mathematical Methods for Knowledge Discovery and Data Mining Book in PDF, ePub and Kindle
"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.
Author | : Harvey J. Miller |
Publisher | : CRC Press |
Total Pages | : 486 |
Release | : 2009-05-27 |
Genre | : Computers |
ISBN | : 1420073982 |
Download Geographic Data Mining and Knowledge Discovery Book in PDF, ePub and Kindle
The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and Spatiotemporal DatabasesSince the publication of the first edition of Geographic Data Mining and Knowledge Discovery, new techniques for geographic data warehousing (GDW), spatial data mining, and geovisualization (GVis) have been developed. In addition, there has bee
Author | : Evangelos Triantaphyllou |
Publisher | : Springer Science & Business Media |
Total Pages | : 371 |
Release | : 2010-06-08 |
Genre | : Computers |
ISBN | : 144191630X |
Download Data Mining and Knowledge Discovery via Logic-Based Methods Book in PDF, ePub and Kindle
The importance of having ef cient and effective methods for data mining and kn- ledge discovery (DM&KD), to which the present book is devoted, grows every day and numerous such methods have been developed in recent decades. There exists a great variety of different settings for the main problem studied by data mining and knowledge discovery, and it seems that a very popular one is formulated in terms of binary attributes. In this setting, states of nature of the application area under consideration are described by Boolean vectors de ned on some attributes. That is, by data points de ned in the Boolean space of the attributes. It is postulated that there exists a partition of this space into two classes, which should be inferred as patterns on the attributes when only several data points are known, the so-called positive and negative training examples. The main problem in DM&KD is de ned as nding rules for recognizing (cl- sifying) new data points of unknown class, i. e. , deciding which of them are positive and which are negative. In other words, to infer the binary value of one more attribute, called the goal or class attribute. To solve this problem, some methods have been suggested which construct a Boolean function separating the two given sets of positive and negative training data points.