Rule extraction from support vector machines:
Saved in:
| Other Authors: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Berlin [u.a.]
Springer
2008
|
| Series: | Studies in computational intelligence
80 |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XII, 262 S. 235 mm x 155 mm |
| ISBN: | 9783540753896 3540753893 |
Staff View
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Record in the Search Index
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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 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author2 | Diederich, Joachim |
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| author_facet | Diederich, Joachim |
| building | Verbundindex |
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| callnumber-first | Q - Science |
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| callnumber-raw | Q325.5 |
| callnumber-search | Q325.5 |
| callnumber-sort | Q 3325.5 |
| callnumber-subject | Q - General Science |
| classification_rvk | ST 300 ST 330 |
| ctrlnum | (OCoLC)255952257 (DE-599)DNB985541709 |
| dewey-full | 006.31 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
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| dewey-search | 006.31 |
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| discipline | Informatik |
| discipline_str_mv | Informatik |
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| index_date | 2024-07-02T20:05:33Z |
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| isbn | 9783540753896 3540753893 |
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| physical | XII, 262 S. 235 mm x 155 mm |
| publishDate | 2008 |
| publishDateSearch | 2008 |
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| publisher | Springer |
| record_format | marc |
| series | Studies in computational intelligence |
| series2 | Studies in computational intelligence |
| 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 |
| volume_link | (DE-604)BV020822171 |
| work_keys_str_mv | AT diederichjoachim ruleextractionfromsupportvectormachines |