A heuristic approach to possibilistic clustering: algorithms and applications:
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Berlin [u.a.]
Springer
2013
|
| Series: | Studies in fuzziness and soft computing
297 |
| Subjects: | |
| Online Access: | BTU01 FHA01 FHI01 FHN01 FHR01 FKE01 FWS01 UBY01 Volltext Inhaltsverzeichnis Abstract |
| Physical Description: | 1 Online-Ressource |
| ISBN: | 9783642355363 |
| DOI: | 10.1007/978-3-642-35536-3 |
Staff View
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Record in the Search Index
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| adam_text | A HEURISTIC APPROACH TO POSSIBILISTIC CLUSTERING: ALGORITHMS AND
APPLICATIONS
/ VIATTCHENIN, DMITRI A.
: 2013
TABLE OF CONTENTS / INHALTSVERZEICHNIS
INTRODUCTION
HEURISTIC ALGORITHMS OF POSSIBILISTIC CLUSTERING
CLUSTERING APPROACHES FOR THE UNCERTAIN DATA
APPLICATIONS OF THE HEURISTIC ALGORITHMS OF POSSIBILISTIC CLUSTERING
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
A HEURISTIC APPROACH TO POSSIBILISTIC CLUSTERING: ALGORITHMS AND
APPLICATIONS
/ VIATTCHENIN, DMITRI A.
: 2013
ABSTRACT / INHALTSTEXT
THE PRESENT BOOK OUTLINES A NEW APPROACH TO POSSIBILISTIC CLUSTERING IN
WHICH THE SOUGHT CLUSTERING STRUCTURE OF THE SET OF OBJECTS IS BASED
DIRECTLY ON THE FORMAL DEFINITION OF FUZZY CLUSTER AND THE POSSIBILISTIC
MEMBERSHIPS ARE DETERMINED DIRECTLY FROM THE VALUES OF THE PAIRWISE
SIMILARITY OF OBJECTS. THE PROPOSED APPROACH CAN BE USED FOR SOLVING
DIFFERENT CLASSIFICATION PROBLEMS. HERE, SOME TECHNIQUES THAT MIGHT BE
USEFUL AT THIS PURPOSE ARE OUTLINED, INCLUDING A METHODOLOGY FOR
CONSTRUCTING A SET OF LABELED OBJECTS FOR A SEMI-SUPERVISED CLUSTERING
ALGORITHM, A METHODOLOGY FOR REDUCING ANALYZED ATTRIBUTE SPACE
DIMENSIONALITY AND A METHODS FOR ASYMMETRIC DATA PROCESSING. MOREOVER,
A TECHNIQUE FOR CONSTRUCTING A SUBSET OF THE MOST APPROPRIATE
ALTERNATIVES FOR A SET OF WEAK FUZZY PREFERENCE RELATIONS, WHICH ARE
DEFINED ON A UNIVERSE OF ALTERNATIVES, IS DESCRIBED IN DETAIL, AND A
METHOD FOR RAPIDLY PROTOTYPING THE MAMDANI’S FUZZY INFERENCE SYSTEMS
IS INTRODUCED. THIS BOOK ADDRESSES ENGINEERS, SCIENTISTS, PROFESSORS,
STUDENTS AND POST-GRADUATE STUDENTS, WHO ARE INTERESTED IN AND WORK WITH
FUZZY CLUSTERING AND ITS APPLICATIONS
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
|
| any_adam_object | 1 |
| author | Viattchenin, Dmitri A. |
| author_facet | Viattchenin, Dmitri A. |
| author_role | aut |
| author_sort | Viattchenin, Dmitri A. |
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| dewey-full | 006.3 |
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| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3 |
| dewey-search | 006.3 |
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| discipline | Informatik |
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| language | English |
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| series | Studies in fuzziness and soft computing |
| series2 | Studies in fuzziness and soft computing |
| spellingShingle | Viattchenin, Dmitri A. A heuristic approach to possibilistic clustering: algorithms and applications Studies in fuzziness and soft computing Ingenieurwissenschaften Künstliche Intelligenz Data mining Artificial intelligence Engineering Fuzzy-Clusteranalyse (DE-588)4802783-2 gnd |
| subject_GND | (DE-588)4802783-2 |
| title | A heuristic approach to possibilistic clustering: algorithms and applications |
| title_auth | A heuristic approach to possibilistic clustering: algorithms and applications |
| title_exact_search | A heuristic approach to possibilistic clustering: algorithms and applications |
| title_full | A heuristic approach to possibilistic clustering: algorithms and applications Dmitri A. Viattchenin |
| title_fullStr | A heuristic approach to possibilistic clustering: algorithms and applications Dmitri A. Viattchenin |
| title_full_unstemmed | A heuristic approach to possibilistic clustering: algorithms and applications Dmitri A. Viattchenin |
| title_short | A heuristic approach to possibilistic clustering: algorithms and applications |
| title_sort | a heuristic approach to possibilistic clustering algorithms and applications |
| topic | Ingenieurwissenschaften Künstliche Intelligenz Data mining Artificial intelligence Engineering Fuzzy-Clusteranalyse (DE-588)4802783-2 gnd |
| topic_facet | Ingenieurwissenschaften Künstliche Intelligenz Data mining Artificial intelligence Engineering Fuzzy-Clusteranalyse |
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