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- World Scientific Publishing Company 2005; US$ 133.00 US$ 121.03
This book describes exciting new opportunities for utilizing robust graph representations of data with common machine learning algorithms. Graphs can model additional information which is often not present in commonly used data representations, such as vectors. more...
- Springer Berlin Heidelberg 2006; US$ 127.37
Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking,... more...
- Elsevier Science 2005; US$ 305.00
This book focuses on dealing with large-scale data, a field commonly referred to as data mining. The book is divided into three sections. The first deals with an introduction to statistical aspects of data mining and machine learning and includes applications to text analysis, computer intrusion detection, and hiding of information in digital files.... more...
- IOS Press 2006; US$ 85.00
With the increased possibilities in modern society for companies and institutions to gather data cheaply and efficiently, the subject of Data Mining has become of increasing importance. This work looks into the different uses of Data Mining, covering the subject of Multi-Relational Data Mining (MRDM), the approach to Structured Data Mining. more...
- Pearson Education 2006; US$ 51.99
The MCSE 70-293 Exam Prep is the most accurate, comprehensive, and up-to-date study guide if you are preparing for one of the four core exams required of this popular Microsoft certification. Updated for R2 versions of the product and the exam, this book serves as both a learning and practice tool. Organized according to the exam objectives, which... more...
- Elsevier Science 2010; US$ 86.95
Are you a data mining analyst, who spends up to 80% of your time assuring data quality, then preparing that data for developing and deploying predictive models? And do you find lots of literature on data mining theory and concepts, but when it comes to practical advice on developing good mining views find little ?how to information? And are you, like... more...
- Elsevier Science 2001; US$ 79.95
Microsoft Data Mining approaches data mining from the particular perspective of IT professionals using Microsoft data management technologies. The author explains the new data mining capabilities in Microsoft's SQL Server 2000 database, Commerce Server, and other products, details the Microsoft OLE DB for Data Mining standard, and gives readers best... more...
- Springer US 2006; US$ 221.86
2. Some Background Information 49 3. Definitions and Terminology 52 4. The One Clause at a Time (OCAT) Approach 54 4. 1 Data Binarization 54 4. 2 The One Clause at a Time (OCAT) Concept 58 4. 3 A Branch-and-Bound Approach for Inferring Clauses 59 4. 4 Inference of the Clauses for the Illustrative Example 62 4. 5 A Polynomial Time Heuristic for Inferring... more...
- Wiley 2007; US$ 134.00 US$ 116.13
The most thorough and up-to-date introduction to data mining techniques using SAS Enterprise Miner. The Sample, Explore, Modify, Model, and Assess (SEMMA) methodology of SAS Enterprise Miner is an extremely valuable analytical tool for making critical business and marketing decisions. Until now, there has been no single, authoritative book that... more...