Data Mining: Concepts and Techniques

EBook Description: Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge.

Intelligent Data Mining � Techniques and Applications" is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications. The main objective of this book is to gather a number of peer-reviewed high quality contributions in the relevant topic areas. The focus is especially on those chapters that provide theoretical/analytical solutions to the problems of real interest in intelligent techniques possibly combined with other traditional tools, for data mining and the corresponding applications to engineers and managers of different industrial sectors.

Statistical Data Mining Using SAS Applications, Second Edition

Statistical Data Mining Using SAS Applications, Second Edition describes statistical data mining concepts and demonstrates the features of user-friendly data mining SAS tools. Integrating the statistical and graphical analysis tools available in SAS systems, the book provides complete statistical data mining solutions without writing SAS program codes or using the point-and-click approach. Each chapter emphasizes step-by-step instructions for using SAS macros and interpreting the results. Compiled data mining SAS macro files are available for download on the author�s website. By following the step-by-step instructions and downloading the SAS macros, analysts can perform complete data mining analysis fast and effectively.
New to the Second Edition�General Features

"Data Engineering: Mining, Information and Intelligence"

It is quite clear that the world is awash in all kinds of data. In fact, the sheer volume of data adds little value to human activity and choices. The key to the vast amounts of data and information available to us is to distill and organize the data into information that we can productively use. Therefore, the most desirable information is that information which can be used to provide insight and intelligence for actionable strategies. DATA ENGINEERING: Mining, Information and Intelligence focuses specifically on applied information-warehousing and data-mining research that is being used or can be used by both academic researchers and industry enterprises. Moreover, the book will be the first to categorize and synthesize the diverse methodologies that are used in these interrelated fields into a structured approach entitled, Data Engineering

"Data Mining and Knowledge Discovery Handbook"

Knowledge Discovery demonstrates intelligent computing at its best, and is the most desirable and interesting end-product of Information Technology. To be able to discover and to extract knowledge from data is a task that many researchers and practitioners are endeavoring to accomplish. There is a lot of hidden knowledge waiting to be discovered � this is the challenge created by today�s abundance of data.

Fundamentals of Data Mining in Genomics and Proteomics

This book aims to present state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. Research and development in genomics and proteomics depend on the analysis and interpretation of large amounts of data generated by high-throughput techniques. To exploit data obtained from experimental and observational studies, life scientists need to understand the analytical techniques and methods from statistics and data mining. These techniques are not easily accessible to life scientists working on genomics and proteomics problems, as the available material is presented from a highly mathematical perspective, favoring formal rigor over conceptual clarity and assessment of practical relevance. This book addresses these issues by adopting an approach focusing on concepts and applications. It presents key analytical techniques for the analysis of genomics and proteomics data by detailing their underlying principles, merits and limitations.

Data Mining - Practical Machine Learning Tools and Techniques

Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining.
*Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects *Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods *Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks-in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization

Data Mining: Concepts, Models, Methods, and Algorithms

Data mining describes the often complex and sophisticated tools used in automatic data analysis such as analyzing a customer's previous buying habits
Emphasizes the selection of appropriate methodologies and data analysis software, as well as parameter tuning
Describes representative state-of-the-art methods and algorithms originating from different disciplines
Offers guidance on how and when to use a particular software tool from among the hundreds offered when faced with a data set to mine

Data Mining: Concepts, Models, Methods, and Algorithms

ata mining describes the often complex and sophisticated tools used in automatic data analysis such as analyzing a customer's previous buying habits

Emphasizes the selection of appropriate methodologies and data analysis software, as well as parameter tuning

Describes representative state-of-the-art methods and algorithms originating from different disciplines

Offers guidance on how and when to use a particular software tool from among the hundreds offered when faced with a data set to mine

"New Fundamental Technologies in Data Mining"

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by �Data Mining� address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data minin

"Exploratory Data Analysis Using Fisher Information"

The basic goal of a research scientist is to understand a given, unknown system. This innovative book develops a systematic approach for achieving this goal. All science is ultimately dependent upon observation which, in turn, requires a flow of information. Fisher information, in particular, is found to provide the key to understanding the system. It is developed as a new tool of exploratory data analysis, and is applied to a wide scope of systems problems. These range from molecules in a gas to biological organisms in their ecologies, to the socio-economic organization of people in their societies, to the physical constants in the universe and, ultimately, to proto-universes in the multiverse.

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