Graphs for Pattern Recognition : Infeasible Systems of Linear Inequalities
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 b...
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| Formato: | Libro |
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De Gruyter
2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1385617&site=ehost-live header: @attributes: shortDbName: nlebk uiTerm: 1385617 longDbName: eBook Collection (EBSCOhost) uiTag: AN controlInfo: bkinfo: btl: Graphs for Pattern Recognition : Infeasible Systems of Linear Inequalities aug: au: Damir Gainanov isbn: 9783110480139 9783110481068 9783110480306 imageinfo: pubinfo: dt: @attributes: year: 2016 month: 01 day: 01 dtAvail: @attributes: year: 2016 month: 11 day: 23 pub: De Gruyter pubContract: De Gruyter place: [N.p.] price: 0.01 limitsGroup: maxCheckoutDays: 1500 pda: N printPagesOffline: 100 printPagesOnline: 100 previewPages: 10000 prePubGroup: dewey: @attributes: class: 516.1 item: 516 .1 lc: @attributes: class: QA295 .G275 2016 item: QA 295 .G275 2016 artinfo: ui: 1385617 960975717 formats: fmt: – @attributes: type: EB doid: NL$1385617$PDF caption: PDF download: Y – @attributes: type: EK doid: NL$1385617$EPUB caption: EPUB download: Y tig: atl: Graphs for Pattern Recognition : Infeasible Systems of Linear Inequalities ptl: Graphs for Pattern Recognition aug: au: Damir Gainanov su: Inequalities (Mathematics) Graph theory sug: subj: MATHEMATICS / Combinatorics COMPUTERS / Image Processing COMPUTERS / Programming / Algorithms MATHEMATICS / Applied MATHEMATICS / Geometry / General MATHEMATICS / Optimization Inequalities (Mathematics) Graph theory ab: 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:PrefacePattern recognition, infeasible systems of linear inequalities, and graphsInfeasible monotone systems of constraintsComplexes, (hyper)graphs, and inequality systemsPolytopes, positive bases, and inequality systemsMonotone Boolean functions, complexes, graphs, and inequality systemsInequality systems, committees, (hyper)graphs, and alternative coversBibliographyList of notationIndex pubtype: eBook doctype: Book ougenre: Book language: English copyright: @attributes: flag: N copyrightText: holdings: @attributes: islocal: N |
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