The Resource Graphs for Pattern Recognition
Graphs for Pattern Recognition
Resource Information
The item Graphs for Pattern Recognition represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Missouri University of Science & Technology Library.This item is available to borrow from 1 library branch.
Resource Information
The item Graphs for Pattern Recognition represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Missouri University of Science & Technology Library.
This item is available to borrow from 1 library branch.
- Summary
- This monograph deals with mathematical constructions that are foundational in such an important area of data mining as pattern recognition. By using combinatorial and graph theoretic techniques, a closer look is taken at infeasible systems of linear inequalities, whose generalized solutions act as building blocks of geometric decision rules for pattern recognition. Infeasible systems of linear inequalities prove to be a key object in pattern recognition problems described in geometric terms thanks to the committee method. Such infeasible systems of inequalities represent an important special subclass of infeasible systems of constraints with a monotonicity property - systems whose multi-indices of feasible subsystems form abstract simplicial complexes (independence systems), which are fundamental objects of combinatorial topology. The methods of data mining and machine learning discussed in this monograph form the foundation of technologies like big data and deep learning, which play a growing role in many areas of human-technology interaction and help to find solutions, better solutions and excellent solutions. Contents: Preface Pattern recognition, infeasible systems of linear inequalities, and graphs Infeasible monotone systems of constraints Complexes, (hyper)graphs, and inequality systems Polytopes, positive bases, and inequality systems Monotone Boolean functions, complexes, graphs, and inequality systems Inequality systems, committees, (hyper)graphs, and alternative covers Bibliography List of notation Index
- Language
- eng
- Label
- Graphs for Pattern Recognition
- Title
- Graphs for Pattern Recognition
- Language
- eng
- Summary
- This monograph deals with mathematical constructions that are foundational in such an important area of data mining as pattern recognition. By using combinatorial and graph theoretic techniques, a closer look is taken at infeasible systems of linear inequalities, whose generalized solutions act as building blocks of geometric decision rules for pattern recognition. Infeasible systems of linear inequalities prove to be a key object in pattern recognition problems described in geometric terms thanks to the committee method. Such infeasible systems of inequalities represent an important special subclass of infeasible systems of constraints with a monotonicity property - systems whose multi-indices of feasible subsystems form abstract simplicial complexes (independence systems), which are fundamental objects of combinatorial topology. The methods of data mining and machine learning discussed in this monograph form the foundation of technologies like big data and deep learning, which play a growing role in many areas of human-technology interaction and help to find solutions, better solutions and excellent solutions. Contents: Preface Pattern recognition, infeasible systems of linear inequalities, and graphs Infeasible monotone systems of constraints Complexes, (hyper)graphs, and inequality systems Polytopes, positive bases, and inequality systems Monotone Boolean functions, complexes, graphs, and inequality systems Inequality systems, committees, (hyper)graphs, and alternative covers Bibliography List of notation Index
- Cataloging source
- IDEBK
- http://library.link/vocab/creatorName
- Gainanov, Damir
- Dewey number
- 516/.1
- Index
- index present
- LC call number
- QA295
- LC item number
- .G275 2016
- Literary form
- non fiction
- Nature of contents
-
- dictionaries
- bibliography
- http://library.link/vocab/subjectName
-
- Inequalities (Mathematics)
- Graph theory
- Deutsche Arbeitsgemeinschaft für Mustererkennung
- MATHEMATICS
- Graph theory
- Inequalities (Mathematics)
- Lineares Ungleichungssystem
- Graphentheorie
- Kombinatorische Optimierung
- Label
- Graphs for Pattern Recognition
- Bibliography note
- Includes bibliographical references (pages 133-140) and index
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Control code
- 960975717
- Dimensions
- unknown
- Extent
- 1 online resource (158)
- Form of item
- online
- Isbn
- 9783110481068
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- http://library.link/vocab/ext/overdrive/overdriveId
- 964181
- Specific material designation
- remote
- System control number
- (OCoLC)960975717
- Label
- Graphs for Pattern Recognition
- Bibliography note
- Includes bibliographical references (pages 133-140) and index
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Control code
- 960975717
- Dimensions
- unknown
- Extent
- 1 online resource (158)
- Form of item
- online
- Isbn
- 9783110481068
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- http://library.link/vocab/ext/overdrive/overdriveId
- 964181
- Specific material designation
- remote
- System control number
- (OCoLC)960975717
Subject
- Deutsche Arbeitsgemeinschaft für Mustererkennung
- Deutsche Arbeitsgemeinschaft für Mustererkennung
- Electronic books
- Graph theory
- Graph theory
- Graphentheorie
- Inequalities (Mathematics)
- Kombinatorische Optimierung
- Lineares Ungleichungssystem
- MATHEMATICS -- Geometry | General
- Inequalities (Mathematics)
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.library.mst.edu/portal/Graphs-for-Pattern-Recognition/KUbAekjpCgE/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.mst.edu/portal/Graphs-for-Pattern-Recognition/KUbAekjpCgE/">Graphs for Pattern Recognition</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.mst.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.mst.edu/">Missouri University of Science & Technology Library</a></span></span></span></span></div>
