Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributio
This book brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluating, interpreting and understanding biometric data. This professional book naturally le
The book "Rough-Granular Computing in Knowledge Discovery and Data Mining" written by Professor Jaroslaw Stepaniuk is dedicated to methods based on a combination of the following three closely related
The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphical components of a document and to extract information. This book is a collection of research papers and st
Elden (numerical analysis, Linkoping U.) uses as examples handwritten digits, text summarization, pagerank computations made famous by a certain very popular search engine (the name of which is now us
Spatio-temporal databases have been the subjects of a significant amount of academic and industrial research, resulting in advances including modeling, indexing and moving of objects and spatio-tempor
This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents a broad, yet in-depth overview of the field of data mining.
This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concept
Awbrey (undergraduate education, Oakland U.) et al. compile 12 essays by contributors from around the world in a variety of fields, from educational psychology to business to teaching and physics. The
This is the first text on pattern recognition to present the Bayesian viewpoint, one that has become increasing popular in the last five years. It presents approximate inference algorithms that permi
"This book covers research topics of data mining on bioinformatics presenting the basics and problems of bioinformatics and applications of data mining technologies pertaining to the field"--Provided
This book presents some of the most recent research results in the area of machine learning and robot perception. The chapters represent new ways of solving real-world problems. The book covers topics
Medical Informatics and biomedical computing have grown in quantum measure over the past decade. An abundance of advances have come to the foreground in this field with the vast amounts of biomedical
Presents the latest and most advanced tools and techniques available for data and web mining strategies with chapters written by leading world experts. Provides practicing engineers and scientists wit
Rather than offering either a purely practical or theoretical context, this text is written by a team of managers and academics, combining theory and practice to create a holistic, and above all reali
Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines.
Uncertainty Handling and Quality Assessment in Data Mining provides an introduction to the application of these concepts in Knowledge Discovery and Data Mining. It reviews the state-of-the-art in unce
* First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches * Addresses the principles of multimedia data compres
Data Mining in Finance presents a comprehensive overview of major algorithmic approaches to predictive data mining, including statistical, neural networks, ruled-based, decision-tree, and fuzzy-log
This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic al
