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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| Format: | Electronic Book Chapter |
| Language: | English |
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De Gruyter
2016
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| Online Access: | DOAB: download the publication DOAB: description of the publication |
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| 100 | 1 | |a Gainanov, Damir |4 auth | |
| 245 | 1 | 0 | |a Graphs for Pattern Recognition. Infeasible Systems of Linear Inequalities |
| 260 | |b De Gruyter |c 2016 | ||
| 300 | |a 1 electronic resource (148 p.) | ||
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| 520 | |a 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 rules for pattern recognition. | ||
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| 546 | |a English | ||
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| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/48863 |7 0 |z DOAB: description of the publication |