Design and analysis of learning classifier systems: a probabilistic approach
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin [u.a.]
Springer
2008
|
| Schriftenreihe: | Studies in computational intelligence
139 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | Literaturverz. S. 251 - 263 |
| Beschreibung: | XIV, 267 S. graph. Darst. |
| ISBN: | 9783540798651 9783540798668 |
Internformat
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Datensatz im Suchindex
| _version_ | 1804137906608013312 |
|---|---|
| adam_text | CONTENTS INTRODUCTION 1 1.1 MACHINE LEARNING 1 1.1.1 COMMON MACHINE
LEARNING TASKS 2 1.1.2 DESIGNING AN UNSUPERVISED LEARNING ALGORITHM 3
1.2 LEARNING CLASSIFIER SYSTEMS 5 1.2.1 A BRIEF OVERVIEW 5 1.2.2
APPLICATIONS AND CURRENT ISSUES 6 1.3 ABOUT THE MODEL-CENTRED APPROACH
TO LCS 7 1.3.1 THE INITIAL APPROACH 7 1.3.2 TAKING A MODEL-CENTRED VIEW
7 1.3.3 SUMMARISING THE APPROACH 8 1.3.4 NOVELTIES 9 1.4 HOW TO READ
THIS BOOK 9 1.4.1 CHAPTER OVERVIEW 9 BACKGROUND 13 2.1 A GENERAL PROBLEM
DESCRIPTION 14 2.2 EARLY LEARNING CLASSIFIER SYSTEMS 10 2.2.1 INITIAL
IDEA 10 2.2.2 THE GENERAL FRAMEWORK 17 2.2.3 INTERACTING SUBSYSTEMS 19
2.2.4 THE GENETIC ALGORITHM IN LCS 19 2.2.5 THE PROBLEMS OF EARLY LCS 20
2.3 THE LCS RENAISSANCE 21 2.3.1 COMPUTING THE PREDICTION 21 2.3.2
LOCALISATION AND REPRESENTATION 22 2.3.3 CLASSIFIERS AS LOCALISED MAPS
FROM INPUT TO OUTPUT 22 2.3.4 RECOVERING THE GLOBAL PREDICTION 23 2.3.5
MICHIGAN-STYLE VS. PITTSBURGH-STYLE LCS 24 2.4 EXISTING THEORY 24 2.4.1
THE HOLISTIC VIEW 24 GESCANNT DURCH BIBLIOGRAFISCHE INFORMATIONEN
HTTP://D-NB.INFO/988160250 DIGITALISIERT DURCH * * * * * * * * * * * * *
* XIV CONTENTS 9.4 STABILITY OF RL WITH LCS 220 9.4.1 STABILITY OF
APPROXIMATE DYNAMIC PROGRAMMING 220 9.4.2 STABILITY ON THE STRUCTURE AND
THE PARAMETER LEARNING LEVEL 221 9.4.3 NON-EXPANSION WITH RESPECT TO |J
* ||OO 223 9.4.4 NON-EXPANSION WITH RESPECT TO || * ||D 225 9.4.5
CONSEQUENCES FOR XCS AND XCSF 227 9.5 FURTHER ISSUES 227 9.5.1 LONG PATH
LEARNING 227 9.5.2 EXPLORATION AND EXPLOITATION 231 9.6 SUMMARY 234 10
CONCLUDING REMARKS 237 A NOTATION 241 B XCS AND XCSF 247 B.I CLASSIFIER
MODEL AND MIXING MODEL 247 B.2 MODEL STRUCTURE SEARCH 248 REFERENCES 251
INDEX 205
|
| adam_txt |
CONTENTS INTRODUCTION 1 1.1 MACHINE LEARNING 1 1.1.1 COMMON MACHINE
LEARNING TASKS 2 1.1.2 DESIGNING AN UNSUPERVISED LEARNING ALGORITHM 3
1.2 LEARNING CLASSIFIER SYSTEMS 5 1.2.1 A BRIEF OVERVIEW 5 1.2.2
APPLICATIONS AND CURRENT ISSUES 6 1.3 ABOUT THE MODEL-CENTRED APPROACH
TO LCS 7 1.3.1 THE INITIAL APPROACH 7 1.3.2 TAKING A MODEL-CENTRED VIEW
7 1.3.3 SUMMARISING THE APPROACH 8 1.3.4 NOVELTIES 9 1.4 HOW TO READ
THIS BOOK 9 1.4.1 CHAPTER OVERVIEW 9 BACKGROUND 13 2.1 A GENERAL PROBLEM
DESCRIPTION 14 2.2 EARLY LEARNING CLASSIFIER SYSTEMS 10 2.2.1 INITIAL
IDEA 10 2.2.2 THE GENERAL FRAMEWORK 17 2.2.3 INTERACTING SUBSYSTEMS 19
2.2.4 THE GENETIC ALGORITHM IN LCS 19 2.2.5 THE PROBLEMS OF EARLY LCS 20
2.3 THE LCS RENAISSANCE 21 2.3.1 COMPUTING THE PREDICTION 21 2.3.2
LOCALISATION AND REPRESENTATION 22 2.3.3 CLASSIFIERS AS LOCALISED MAPS
FROM INPUT TO OUTPUT 22 2.3.4 RECOVERING THE GLOBAL PREDICTION 23 2.3.5
MICHIGAN-STYLE VS. PITTSBURGH-STYLE LCS 24 2.4 EXISTING THEORY 24 2.4.1
THE HOLISTIC VIEW 24 GESCANNT DURCH BIBLIOGRAFISCHE INFORMATIONEN
HTTP://D-NB.INFO/988160250 DIGITALISIERT DURCH * * * * * * * * * * * * *
* XIV CONTENTS 9.4 STABILITY OF RL WITH LCS 220 9.4.1 STABILITY OF
APPROXIMATE DYNAMIC PROGRAMMING 220 9.4.2 STABILITY ON THE STRUCTURE AND
THE PARAMETER LEARNING LEVEL 221 9.4.3 NON-EXPANSION WITH RESPECT TO |J
* ||OO 223 9.4.4 NON-EXPANSION WITH RESPECT TO || * ||D 225 9.4.5
CONSEQUENCES FOR XCS AND XCSF 227 9.5 FURTHER ISSUES 227 9.5.1 LONG PATH
LEARNING 227 9.5.2 EXPLORATION AND EXPLOITATION 231 9.6 SUMMARY 234 10
CONCLUDING REMARKS 237 A NOTATION 241 B XCS AND XCSF 247 B.I CLASSIFIER
MODEL AND MIXING MODEL 247 B.2 MODEL STRUCTURE SEARCH 248 REFERENCES 251
INDEX 205 |
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| discipline | Informatik |
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| spelling | Drugowitsch, Jan Verfasser aut Design and analysis of learning classifier systems a probabilistic approach Jan Drugowitsch Berlin [u.a.] Springer 2008 XIV, 267 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Studies in computational intelligence 139 Literaturverz. S. 251 - 263 Apprentissage automatique Machine learning Soft Computing (DE-588)4455833-8 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Automatische Klassifikation (DE-588)4120957-6 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Automatische Klassifikation (DE-588)4120957-6 s Maschinelles Lernen (DE-588)4193754-5 s Soft Computing (DE-588)4455833-8 s DE-604 Studies in computational intelligence 139 (DE-604)BV020822171 139 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016662719&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Drugowitsch, Jan Design and analysis of learning classifier systems a probabilistic approach Studies in computational intelligence Apprentissage automatique Machine learning Soft Computing (DE-588)4455833-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Automatische Klassifikation (DE-588)4120957-6 gnd |
| subject_GND | (DE-588)4455833-8 (DE-588)4193754-5 (DE-588)4120957-6 (DE-588)4143413-4 |
| title | Design and analysis of learning classifier systems a probabilistic approach |
| title_auth | Design and analysis of learning classifier systems a probabilistic approach |
| title_exact_search | Design and analysis of learning classifier systems a probabilistic approach |
| title_exact_search_txtP | Design and analysis of learning classifier systems a probabilistic approach |
| title_full | Design and analysis of learning classifier systems a probabilistic approach Jan Drugowitsch |
| title_fullStr | Design and analysis of learning classifier systems a probabilistic approach Jan Drugowitsch |
| title_full_unstemmed | Design and analysis of learning classifier systems a probabilistic approach Jan Drugowitsch |
| title_short | Design and analysis of learning classifier systems |
| title_sort | design and analysis of learning classifier systems a probabilistic approach |
| title_sub | a probabilistic approach |
| topic | Apprentissage automatique Machine learning Soft Computing (DE-588)4455833-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Automatische Klassifikation (DE-588)4120957-6 gnd |
| topic_facet | Apprentissage automatique Machine learning Soft Computing Maschinelles Lernen Automatische Klassifikation Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016662719&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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