Classification The Ubiquitous Challenge
Download Classification The Ubiquitous Challenge PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Classification The Ubiquitous Challenge book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Cooperation in Classification and Data Analysis
Author: Akinori Okada
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-06-17
This volume presents theories, models, algorithms, and applications in clustering, classification, and visualization. It also includes applications of clustering, classification, and visualization in various fields such as marketing, recommendation system, biology, sociology, and social survey. The contributions give insight into new models and concepts and show the variety of research in clustering, classification, and visualization.
Challenges at the Interface of Data Analysis, Computer Science, and Optimization
Author: Wolfgang Gaul
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-02-09
This volume provides approaches and solutions to challenges occurring at the interface of research fields such as data analysis, computer science, operations research, and statistics. It includes theoretically oriented contributions as well as papers from various application areas, where knowledge from different research directions is needed to find the best possible interpretation of data for the underlying problem situations. Beside traditional classification research, the book focuses on current interests in fields such as the analysis of social relationships as well as statistical musicology.
Statistical Network Analysis: Models, Issues, and New Directions
This book constitutes the thoroughly refereed post-proceedings of the International Workshop on Statistical Network Analysis: Models, Issues, and New Directions held in Pittsburgh, PA, USA in June 2006 as associated event of the 23rd International Conference on Machine Learning, ICML 2006. It covers probabilistic methods for network analysis, paying special attention to model design and computational issues of learning and inference.