Verfügbarkeit: Rule extraction from support vector machines

Rule extraction from support vector machines:

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Bibliographische Detailangaben
Weitere Verfasser:	Diederich, Joachim (HerausgeberIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	Berlin [u.a.] Springer 2008
Schriftenreihe:	Studies in computational intelligence 80
Schlagworte:	Machine learning Support-Vektor-Maschine Maschinelles Lernen Aufsatzsammlung Patentschrift
Online-Zugang:	Inhaltsverzeichnis
Beschreibung:	XII, 262 S. 235 mm x 155 mm
ISBN:	9783540753896 3540753893

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MARC


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Datensatz im Suchindex

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adam_text	CONTENTS PART I INTRODUCTION RULE EXTRACTION FROM SUPPORT VECTOR MACHINES: AN INTRODUCTION JOACHIM DIEDERICH 3 1 EXPLANATION: THE FOUNDATIONS 3 1.1 FORMS OF EXPLANATION 4 1.2 ANALOGY AS A FORM OF EXPLANATION 5 1.3 EXPLANATION-BASED GENERALIZATION 6 1.4 HOW AND WHY EXPLANATIONS 7 1.5 GENERATING OR IDENTIFYING THE BEST EXPLANATION 8 2 RULE EXTRACTION FROM SUPPORT VECTOR MACHINES: AHNS AND SIGNIFICANCE 8 2.1 PROVISION OF A USER EXPLANATION CAPABILITY 9 2.2 TRANSPARENCY 10 2.3 SOFTWARE VERIFICATION 10 2.4 IMPROVING GENERALISATION 11 2.5 DATA EXPLORATION AND THE INDUCTION OF SCIENTIFIC THEORIES 11 3 TRANSLUCENCY AND RULE QUALITY 11 3.1 THE NEURAL NETWORK CASE 12 3.2 TRANSLUCENCY AND RULE QUALITY APPLIED TO RULE EXTRACTION FROM SVMS 13 4 AN ALTERNATIVE VIEW ON RULE EXTRACTION: INFORMATION RETRIEVAL .... 14 5 A CASE STUDY 16 6 A CLASSIFICATION SYSTEM FOR RULE EXTRACTION FROM SVMS 26 7 CONCLUSIONS AND FUTURE CHALLENGES 28 8 ACKNOWLEDGEMENTS 30 REFERENCES 30 GESCANNT DURCH BIBLIOGRAFISCHE INFORMATIONEN HTTP://D-NB.INFO/985541709 DIGITALISIERT DURCH * * * * * * * * * * XII CONTENTS 2.2 PROTEIN SECOND STRUCTURE PREDICTION WITH SVM.DT 231 2.3 TRANSMEMBRANE SEGMENTS PREDICTION AND UNDERSTANDING USING SVM-DT 235 3 EXTRACTING RULE FROM SVM BASED ON ASSOCIATION RULE 238 3.1 ASSOCIATION RULE BASED METHOD 238 3.2 ASSOCIATION RULE MINING 239 4 RULE CLUSTERING AND SUPER_RULE GENERATION 244 5 CONCLUSIONS 247 6 ACKNOWLEDGEMENTS 249 REFERENCES 249 SUBJECT INDEX 253 AUTHOR INDEX 261
adam_txt	CONTENTS PART I INTRODUCTION RULE EXTRACTION FROM SUPPORT VECTOR MACHINES: AN INTRODUCTION JOACHIM DIEDERICH 3 1 EXPLANATION: THE FOUNDATIONS 3 1.1 FORMS OF EXPLANATION 4 1.2 ANALOGY AS A FORM OF EXPLANATION 5 1.3 EXPLANATION-BASED GENERALIZATION 6 1.4 HOW AND WHY EXPLANATIONS 7 1.5 GENERATING OR IDENTIFYING THE BEST EXPLANATION 8 2 RULE EXTRACTION FROM SUPPORT VECTOR MACHINES: AHNS AND SIGNIFICANCE 8 2.1 PROVISION OF A "USER EXPLANATION" CAPABILITY 9 2.2 TRANSPARENCY 10 2.3 SOFTWARE VERIFICATION 10 2.4 IMPROVING GENERALISATION 11 2.5 DATA EXPLORATION AND THE INDUCTION OF SCIENTIFIC THEORIES 11 3 TRANSLUCENCY AND RULE QUALITY 11 3.1 THE NEURAL NETWORK CASE 12 3.2 TRANSLUCENCY AND RULE QUALITY APPLIED TO RULE EXTRACTION FROM SVMS 13 4 AN ALTERNATIVE VIEW ON RULE EXTRACTION: INFORMATION RETRIEVAL . 14 5 A CASE STUDY 16 6 A CLASSIFICATION SYSTEM FOR RULE EXTRACTION FROM SVMS 26 7 CONCLUSIONS AND FUTURE CHALLENGES 28 8 ACKNOWLEDGEMENTS 30 REFERENCES 30 GESCANNT DURCH BIBLIOGRAFISCHE INFORMATIONEN HTTP://D-NB.INFO/985541709 DIGITALISIERT DURCH * * * * * * * * * * XII CONTENTS 2.2 PROTEIN SECOND STRUCTURE PREDICTION WITH SVM.DT 231 2.3 TRANSMEMBRANE SEGMENTS PREDICTION AND UNDERSTANDING USING SVM-DT 235 3 EXTRACTING RULE FROM SVM BASED ON ASSOCIATION RULE 238 3.1 ASSOCIATION RULE BASED METHOD 238 3.2 ASSOCIATION RULE MINING 239 4 RULE CLUSTERING AND SUPER_RULE GENERATION 244 5 CONCLUSIONS 247 6 ACKNOWLEDGEMENTS 249 REFERENCES 249 SUBJECT INDEX 253 AUTHOR INDEX 261
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spelling	Rule extraction from support vector machines Joachim Diederich (ed.) Berlin [u.a.] Springer 2008 XII, 262 S. 235 mm x 155 mm txt rdacontent n rdamedia nc rdacarrier Studies in computational intelligence 80 Machine learning Support-Vektor-Maschine (DE-588)4505517-8 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content (DE-588)4173536-5 Patentschrift gnd-content Maschinelles Lernen (DE-588)4193754-5 s Support-Vektor-Maschine (DE-588)4505517-8 s DE-604 Diederich, Joachim (DE-588)110823087 edt Studies in computational intelligence 80 (DE-604)BV020822171 80 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016379824&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
spellingShingle	Rule extraction from support vector machines Studies in computational intelligence Machine learning Support-Vektor-Maschine (DE-588)4505517-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd
subject_GND	(DE-588)4505517-8 (DE-588)4193754-5 (DE-588)4143413-4 (DE-588)4173536-5
title	Rule extraction from support vector machines
title_auth	Rule extraction from support vector machines
title_exact_search	Rule extraction from support vector machines
title_exact_search_txtP	Rule extraction from support vector machines
title_full	Rule extraction from support vector machines Joachim Diederich (ed.)
title_fullStr	Rule extraction from support vector machines Joachim Diederich (ed.)
title_full_unstemmed	Rule extraction from support vector machines Joachim Diederich (ed.)
title_short	Rule extraction from support vector machines
title_sort	rule extraction from support vector machines
topic	Machine learning Support-Vektor-Maschine (DE-588)4505517-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd
topic_facet	Machine learning Support-Vektor-Maschine Maschinelles Lernen Aufsatzsammlung Patentschrift
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016379824&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
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work_keys_str_mv	AT diederichjoachim ruleextractionfromsupportvectormachines

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