A timely convergence of two widely used disciplines Random Graphs for Statistical Pattern Recognition is the first book to address the topic of random graphs as it applies to statistical pattern recognition. Both topics are of vital interest to researchers in various mathematical and statistical fields and have never before been treated together in one book. The use of data random graphs in pattern recognition in clustering and classification is discussed, and the applications for both disciplines are enhanced with new tools for the statistical pattern recognition community. New and interesting applications for random graph users are also introduced. This important addition to statistical literature features: Information that previously has been available only through scattered journal articles Practical tools and techniques for a wide range of real-world applications New perspectives on the relationship between pattern recognition and computational geometry Numerous experimental problems to encourage practical applications With its comprehensive coverage of two timely fields, enhanced with many references and real-world examples, Random Graphs for Statistical Pattern Recognition is a valuable resource for industry professionals and students alike.... in Data: An Introduction to Cluster Analysis KEDEM and FOKIANOS - Regression Models for Time Series Analysis ... Models: From Data to Decisions KLUGMAN, PANJER, and WILLMOT a#39; Solutions Manual to Accompany Loss Models: Fromanbsp;...
|Title||:||Random Graphs for Statistical Pattern Recognition|
|Author||:||David J. Marchette|
|Publisher||:||John Wiley & Sons - 2005-02-11|