This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by...
Overcoming many challenges, data mining has already established discipline capability in many domains. discusses advances in modern data mining research in today's rapidly growing global and technological...
Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools....
"…a book with many nice features that has elements of interest for …every subset of the intended audience…"
(Journal of the American Statistical Association, September 2006)
"The author's style is consistently readable. Stripping out all but the barest essential...
There is a large increase in the amount of information available on the World Wide Web and also in the number of online databases. This information abundance increases the complexity of locating relevant information. Such complexity drives the need for improved and intelligent systems for search and information retrieval. Intelligent Agents are...
An overview of the multidisciplinary field of data mining, this book focuses specifically on new methodologies and case studies. Included are case studies written by 44 leading scientists and talented young scholars from seven different countries. Topics covered include data mining based on rough sets, the impact of missing data, and mining free...
This volume contains nineteen research papers belonging to the
areas of computational statistics, data mining, and their applications. Those papers, all written specifically for this volume, are their authors’ contributions to honour and celebrate Professor Jacek Koronacki on the occcasion of his 70th birthday. The
This book demonstrates the measurement, monitoring, mapping, and modeling of forest resources. It explores state-of-the-art techniques based on open-source software & R statistical programming and modeling specifically, with a focus on the recent trends in data mining/machine learning techniques and robust modeling in forest resources....
Being the de-facto standard for data representation and exchange over the Web, XML (Extensible Markup Language) allows the easy development of applications that exchange data over the Web. This creates a set of data management requirements involving XML. XML and related standards have been extensively applied in many business, service, and...
Surface and Underground Excavations – Methods, Techniques and Equipment (2nd edition) covers the latest technologies and developments in the excavation arena at any locale: surface or underground. In the first few chapters, unit operations are discussed and subsequently, excavation techniques are described for various operations:...
Concepts like ubiquitous computing and ambient intelligence that exploit increasingly
interconnected networks and mobility put new requirements on data
management. An important element in the connected world is that data will
be accessible anytime anywhere. This also has its downside in that it becomes
easier to get unauthorized data...
