Graphs for pattern recognition : : infeasible systems of linear inequalities / / Damir Gainanov.

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...

Full description

Saved in:
Bibliographic Details
VerfasserIn:
Place / Publishing House:Berlin, [Germany] ;, Boston, [Massachusetts] : : De Gruyter,, 2016.
©2016
Year of Publication:2016
Edition:1st ed.
Language:German
English
Physical Description:1 online resource (x, 147 pages)
Tags: Add Tag
No Tags, Be the first to tag this record!
id 993543685804498
ctrlnum (CKB)3850000000001073
(EBL)4718418
(OCoLC)962793042
(DE-B1597)466925
(OCoLC)951141809
(OCoLC)963114749
(DE-B1597)9783110481068
(Au-PeEL)EBL4718418
(CaPaEBR)ebr11283245
(CaONFJC)MIL964181
(OCoLC)961059086
(ScCtBLL)a80371dd-766f-4802-9ff9-c024f7263329
(oapen)https://directory.doabooks.org/handle/20.500.12854/48863
(CaSebORM)9783110480306
(MiAaPQ)EBC4718418
(EXLCZ)993850000000001073
collection bib_alma
record_format marc
spelling Gainanov, Damir (Damir N.), author.
Graphs for pattern recognition : infeasible systems of linear inequalities / Damir Gainanov.
1st ed.
De Gruyter 2016
Berlin, [Germany] ; Boston, [Massachusetts] : De Gruyter, 2016.
©2016
1 online resource (x, 147 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
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
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
This eBook is made available Open Access. Unless otherwise specified in the content, the work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) license: https://creativecommons.org/licenses/by-nc-nd/3.0 https://www.degruyter.com/dg/page/open-access-policy
In English.
Includes bibliographical references and index.
Description based on print version record.
Inequalities (Mathematics)
Graph theory.
3-11-048013-1
language German
English
format eBook
author Gainanov, Damir
spellingShingle Gainanov, Damir
Graphs for pattern recognition : infeasible systems of linear inequalities /
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
author_facet Gainanov, Damir
author_variant d g dg
author_fuller (Damir N.),
author_role VerfasserIn
author_sort Gainanov, Damir
title Graphs for pattern recognition : infeasible systems of linear inequalities /
title_sub infeasible systems of linear inequalities /
title_full Graphs for pattern recognition : infeasible systems of linear inequalities / Damir Gainanov.
title_fullStr Graphs for pattern recognition : infeasible systems of linear inequalities / Damir Gainanov.
title_full_unstemmed Graphs for pattern recognition : infeasible systems of linear inequalities / Damir Gainanov.
title_auth Graphs for pattern recognition : infeasible systems of linear inequalities /
title_alt 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
title_new Graphs for pattern recognition :
title_sort graphs for pattern recognition : infeasible systems of linear inequalities /
publisher De Gruyter
De Gruyter,
publishDate 2016
physical 1 online resource (x, 147 pages)
edition 1st ed.
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
isbn 3-11-048030-1
3-11-048106-5
3-11-048013-1
callnumber-first Q - Science
callnumber-subject QA - Mathematics
callnumber-label QA295
callnumber-sort QA 3295 G275 42016
illustrated Not Illustrated
dewey-hundreds 500 - Science
dewey-tens 510 - Mathematics
dewey-ones 516 - Geometry
dewey-full 516/.1
dewey-sort 3516 11
dewey-raw 516/.1
dewey-search 516/.1
oclc_num 962793042
951141809
963114749
961059086
work_keys_str_mv AT gainanovdamir graphsforpatternrecognitioninfeasiblesystemsoflinearinequalities
status_str n
ids_txt_mv (CKB)3850000000001073
(EBL)4718418
(OCoLC)962793042
(DE-B1597)466925
(OCoLC)951141809
(OCoLC)963114749
(DE-B1597)9783110481068
(Au-PeEL)EBL4718418
(CaPaEBR)ebr11283245
(CaONFJC)MIL964181
(OCoLC)961059086
(ScCtBLL)a80371dd-766f-4802-9ff9-c024f7263329
(oapen)https://directory.doabooks.org/handle/20.500.12854/48863
(CaSebORM)9783110480306
(MiAaPQ)EBC4718418
(EXLCZ)993850000000001073
carrierType_str_mv cr
is_hierarchy_title Graphs for pattern recognition : infeasible systems of linear inequalities /
_version_ 1798003760690102272
fullrecord <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>04397nam a2200685 i 4500</leader><controlfield tag="001">993543685804498</controlfield><controlfield tag="005">20240501143910.0</controlfield><controlfield tag="006">m o d | </controlfield><controlfield tag="007">cr#cn#nnn|||||</controlfield><controlfield tag="008">161028t20162016gw ob 001 0 ger d</controlfield><datafield tag="019" ind1=" " ind2=" "><subfield code="a">(OCoLC)963114749</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">3-11-048030-1</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">3-11-048106-5</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1515/9783110481068</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CKB)3850000000001073</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EBL)4718418</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)962793042</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-B1597)466925</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)951141809</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)963114749</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-B1597)9783110481068</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(Au-PeEL)EBL4718418</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CaPaEBR)ebr11283245</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CaONFJC)MIL964181</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)961059086</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ScCtBLL)a80371dd-766f-4802-9ff9-c024f7263329</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(oapen)https://directory.doabooks.org/handle/20.500.12854/48863</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CaSebORM)9783110480306</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(MiAaPQ)EBC4718418</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(EXLCZ)993850000000001073</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">MiAaPQ</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="e">pn</subfield><subfield code="c">MiAaPQ</subfield><subfield code="d">MiAaPQ</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="044" ind1=" " ind2=" "><subfield code="a">gw</subfield><subfield code="c">DE</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">QA295</subfield><subfield code="b">.G275 2016</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">COM012050</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">COM051300</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">MAT003000</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">MAT012000</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">MAT036000</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="072" ind1=" " ind2="7"><subfield code="a">MAT042000</subfield><subfield code="2">bisacsh</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">516/.1</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Gainanov, Damir</subfield><subfield code="q">(Damir N.),</subfield><subfield code="e">author.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Graphs for pattern recognition :</subfield><subfield code="b">infeasible systems of linear inequalities /</subfield><subfield code="c">Damir Gainanov.</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">1st ed.</subfield></datafield><datafield tag="260" ind1=" " ind2=" "><subfield code="b">De Gruyter</subfield><subfield code="c">2016</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Berlin, [Germany] ;</subfield><subfield code="a">Boston, [Massachusetts] :</subfield><subfield code="b">De Gruyter,</subfield><subfield code="c">2016.</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">©2016</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource (x, 147 pages)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">computer</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="505" ind1="0" ind2="0"><subfield code="t">Frontmatter -- </subfield><subfield code="t">Preface -- </subfield><subfield code="t">Contents -- </subfield><subfield code="t">1. Pattern recognition, infeasible systems of linear inequalities, and graphs -- </subfield><subfield code="t">2. Complexes, (hyper)graphs, and inequality systems -- </subfield><subfield code="t">3. Polytopes, positive bases, and inequality systems -- </subfield><subfield code="t">4. Monotone Boolean functions, complexes, graphs, and inequality systems -- </subfield><subfield code="t">5. Inequality systems, committees, (hyper)graphs, and alternative covers -- </subfield><subfield code="t">Bibliography -- </subfield><subfield code="t">List of notation -- </subfield><subfield code="t">Index</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">This eBook is made available Open Access. Unless otherwise specified in the content, the work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) license: </subfield><subfield code="u">https://creativecommons.org/licenses/by-nc-nd/3.0 </subfield><subfield code="u">https://www.degruyter.com/dg/page/open-access-policy</subfield></datafield><datafield tag="546" ind1=" " ind2=" "><subfield code="a">In English.</subfield></datafield><datafield tag="504" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references and index.</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Description based on print version record.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Inequalities (Mathematics)</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Graph theory.</subfield></datafield><datafield tag="776" ind1=" " ind2=" "><subfield code="z">3-11-048013-1</subfield></datafield><datafield tag="906" ind1=" " ind2=" "><subfield code="a">BOOK</subfield></datafield><datafield tag="ADM" ind1=" " ind2=" "><subfield code="b">2024-05-03 04:20:13 Europe/Vienna</subfield><subfield code="f">system</subfield><subfield code="c">marc21</subfield><subfield code="a">2016-07-09 16:49:08 Europe/Vienna</subfield><subfield code="g">false</subfield></datafield><datafield tag="AVE" ind1=" " ind2=" "><subfield code="i">DOAB Directory of Open Access Books</subfield><subfield code="P">DOAB Directory of Open Access Books</subfield><subfield code="x">https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&amp;portfolio_pid=5339620750004498&amp;Force_direct=true</subfield><subfield code="Z">5339620750004498</subfield><subfield code="b">Available</subfield><subfield code="8">5339620750004498</subfield></datafield><datafield tag="AVE" ind1=" " ind2=" "><subfield code="i">DOAB Directory of Open Access Books</subfield><subfield code="P">DOAB Directory of Open Access Books</subfield><subfield code="x">https://eu02.alma.exlibrisgroup.com/view/uresolver/43ACC_OEAW/openurl?u.ignore_date_coverage=true&amp;portfolio_pid=5337378310004498&amp;Force_direct=true</subfield><subfield code="Z">5337378310004498</subfield><subfield code="b">Available</subfield><subfield code="8">5337378310004498</subfield></datafield></record></collection>