|
![]() |
|||
|
||||
OverviewData mining is used today in many different fields including banking, financial analysis of markets, insurance and private health sectors, education, industrial processes, medicine, biology, bioengineering and telecommunication. But regardless of the field in which it is applied, the core concepts and tasks of data mining do not require nor domain-specific knowledge, nor advanced mathematical treatments. SAS Data Mining presents the most common techniques used in SAS data mining in a simple and easy to understand way using SAS Enterprise Miner, regardless of the specific field you're working in, and without needing to draw on complicated mathematical algorithms. SAS Data Mining therefore describes data mining techniques to you in accessible language and clear, practical, hands-on examples and exercises. Each chapter presents a data mining case study, including the results of the case study, you've built and an interpretation of its results, which is so vital of course to your data mining work. SAS Data Mining begins with an introduction to data mining data and its distinct phases. You'll then learn how to develop the initial phases which include the selection of information, data exploration, data cleansing, transformation of data, and related issues. After these initial data mining phases, this book goes into practical, hands-on detail on both predictive and descriptive data mining techniques. The predictive techniques you'll learn about cover regression, discriminant analysis, decision trees, neural networks, and other model-based techniques. The descriptive techniques then work with variable dimension reduction techniques, techniques of classification and segmentation (clustering), and exploratory data analysis techniques. Full Product DetailsAuthor: Cesar LopezPublisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Imprint: APress ISBN: 9781484203026ISBN 10: 148420302 Pages: 360 Publication Date: 17 December 2014 Audience: College/higher education , Postgraduate, Research & Scholarly Format: Paperback Publisher's Status: Active Availability: Available To Order ![]() We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of Contents1. Data Mining Concepts, Techniques, and Systems 2. The Selection Phase in the Data Mining Process 3. Introducing SAS Enterprise Miner 4. The Selection Phase in SAS Enterprise Miner 5. The Exploration Phase in Data Mining 6. The Exploration Phase with SAS Enterprise Miner 7. Cleansing and Transforming Data 8. Cleansing and Transforming Data in SAS Enterprise Miner 9. Data Mining Phase - Predictive Techniques 10. Predictive Techniques with SAS Enterprise Miner 11. Decision Trees and Cluster Analysis 12. Decision Trees and Cluster Analysis with SAS Enterprise Miner 13. Neural Networks with SAS Enterprise MinerReviewsAuthor InformationCesar Perez Lopez is a Professor at the Department of Statistics and Operations Research at the University of Madrid. Cesar Perez Lopez is also a Mathematician and Economist at the National Statistics Institute (INE) in Madrid, a body which belongs to the Superior Systems and Information Technology Department of the Spanish Government. Cesar also currently works at the Institute for Fiscal Studies in Madrid. Tab Content 6Author Website:Countries AvailableAll regions |