Graphs for pattern recognition : infeasible systems of linear inequalities /

Data mining and pattern recognition are areas based on the mathematical constructions discussed in this monograph. By using combinatorial and graph theoretical techniques, it is shown how to tackle infeasible systems of linear inequalities. These are, in turn, building blocks of geometric decision r...

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Bibliographic Details
Main Author:	Gainanov, Damir (Damir N.) (Author)
Corporate Author:	Walter de Gruyter & Co
Format:	eBook
Language:	German
Published:	Berlin : De Gruyter, [2016]
Subjects:	Deutsche Arbeitsgemeinschaft für Mustererkennung Inequalities (Mathematics) Graph theory. Inégalités (Mathématiques) MATHEMATICS > Geometry > General. Graph theory Lineares Ungleichungssystem Graphentheorie Kombinatorische Optimierung Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Frontmatter
Preface
Contents
1. Pattern recognition, infeasible systems of linear inequalities, and graphs
2. Complexes, (hyper)graphs, and inequality systems
3. Polytopes, positive bases, and inequality systems
4. Monotone Boolean functions, complexes, graphs, and inequality systems
5. Inequality systems, committees, (hyper)graphs, and alternative covers
Bibliography
List of notation
Index.