Rough Set Methods and Applications: New Developments in Knowledge Discovery in Information Systems
Rough set approach to reasoning under uncertainty is based on inducing knowledge representation from data under constraints expressed by discernibility or, more generally, similarity of objects. Knowledge derived by this approach consists of reducts, decision or association rules, dependencies, temp...
Gespeichert in:
Weitere Verfasser: | , , |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Heidelberg
Physica-Verlag HD
2000
|
Schriftenreihe: | Studies in Fuzziness and Soft Computing
56 |
Schlagworte: | |
Online-Zugang: | FHI01 BTU01 Volltext |
Zusammenfassung: | Rough set approach to reasoning under uncertainty is based on inducing knowledge representation from data under constraints expressed by discernibility or, more generally, similarity of objects. Knowledge derived by this approach consists of reducts, decision or association rules, dependencies, templates, or classifiers. This monograph presents the state of the art of this area. The reader will find here a deep theoretical discussion of relevant notions and ideas as well as rich inventory of algorithmic and heuristic tools for knowledge discovery by rough set methods. An extensive bibliography will help the reader to get an acquaintance with this rapidly growing area of research |
Beschreibung: | 1 Online-Ressource (X, 683 p) |
ISBN: | 9783790818406 |
DOI: | 10.1007/978-3-7908-1840-6 |
Internformat
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520 | |a Rough set approach to reasoning under uncertainty is based on inducing knowledge representation from data under constraints expressed by discernibility or, more generally, similarity of objects. Knowledge derived by this approach consists of reducts, decision or association rules, dependencies, templates, or classifiers. This monograph presents the state of the art of this area. The reader will find here a deep theoretical discussion of relevant notions and ideas as well as rich inventory of algorithmic and heuristic tools for knowledge discovery by rough set methods. An extensive bibliography will help the reader to get an acquaintance with this rapidly growing area of research | ||
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Datensatz im Suchindex
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any_adam_object | |
author2 | Polkowski, Lech Tsumoto, Shusaku Lin, Tsau Y. |
author2_role | edt edt edt |
author2_variant | l p lp s t st t y l ty tyl |
author_facet | Polkowski, Lech Tsumoto, Shusaku Lin, Tsau Y. |
building | Verbundindex |
bvnumber | BV045149585 |
collection | ZDB-2-ENG |
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dewey-full | 006.3 |
dewey-hundreds | 000 - Computer science, information, general works |
dewey-ones | 006 - Special computer methods |
dewey-raw | 006.3 |
dewey-search | 006.3 |
dewey-sort | 16.3 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Informatik |
doi_str_mv | 10.1007/978-3-7908-1840-6 |
format | Electronic eBook |
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indexdate | 2024-07-10T08:10:04Z |
institution | BVB |
isbn | 9783790818406 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030539284 |
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physical | 1 Online-Ressource (X, 683 p) |
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publisher | Physica-Verlag HD |
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series2 | Studies in Fuzziness and Soft Computing |
spelling | Rough Set Methods and Applications New Developments in Knowledge Discovery in Information Systems edited by Lech Polkowski, Shusaku Tsumoto, Tsau Y. Lin Heidelberg Physica-Verlag HD 2000 1 Online-Ressource (X, 683 p) txt rdacontent c rdamedia cr rdacarrier Studies in Fuzziness and Soft Computing 56 Rough set approach to reasoning under uncertainty is based on inducing knowledge representation from data under constraints expressed by discernibility or, more generally, similarity of objects. Knowledge derived by this approach consists of reducts, decision or association rules, dependencies, templates, or classifiers. This monograph presents the state of the art of this area. The reader will find here a deep theoretical discussion of relevant notions and ideas as well as rich inventory of algorithmic and heuristic tools for knowledge discovery by rough set methods. An extensive bibliography will help the reader to get an acquaintance with this rapidly growing area of research Computer Science Artificial Intelligence (incl. Robotics) Mathematical Logic and Formal Languages IT in Business Computer science Information technology Business / Data processing Mathematical logic Artificial intelligence Polkowski, Lech edt Tsumoto, Shusaku edt Lin, Tsau Y. edt Erscheint auch als Druck-Ausgabe 9783662003763 https://doi.org/10.1007/978-3-7908-1840-6 Verlag URL des Erstveröffentlichers Volltext |
spellingShingle | Rough Set Methods and Applications New Developments in Knowledge Discovery in Information Systems Computer Science Artificial Intelligence (incl. Robotics) Mathematical Logic and Formal Languages IT in Business Computer science Information technology Business / Data processing Mathematical logic Artificial intelligence |
title | Rough Set Methods and Applications New Developments in Knowledge Discovery in Information Systems |
title_auth | Rough Set Methods and Applications New Developments in Knowledge Discovery in Information Systems |
title_exact_search | Rough Set Methods and Applications New Developments in Knowledge Discovery in Information Systems |
title_full | Rough Set Methods and Applications New Developments in Knowledge Discovery in Information Systems edited by Lech Polkowski, Shusaku Tsumoto, Tsau Y. Lin |
title_fullStr | Rough Set Methods and Applications New Developments in Knowledge Discovery in Information Systems edited by Lech Polkowski, Shusaku Tsumoto, Tsau Y. Lin |
title_full_unstemmed | Rough Set Methods and Applications New Developments in Knowledge Discovery in Information Systems edited by Lech Polkowski, Shusaku Tsumoto, Tsau Y. Lin |
title_short | Rough Set Methods and Applications |
title_sort | rough set methods and applications new developments in knowledge discovery in information systems |
title_sub | New Developments in Knowledge Discovery in Information Systems |
topic | Computer Science Artificial Intelligence (incl. Robotics) Mathematical Logic and Formal Languages IT in Business Computer science Information technology Business / Data processing Mathematical logic Artificial intelligence |
topic_facet | Computer Science Artificial Intelligence (incl. Robotics) Mathematical Logic and Formal Languages IT in Business Computer science Information technology Business / Data processing Mathematical logic Artificial intelligence |
url | https://doi.org/10.1007/978-3-7908-1840-6 |
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