Feature extraction in regression and classification with structured predictors:
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis Book |
| Language: | English |
| Published: |
Göttingen
Cuvillier
2011
|
| Edition: | 1. Aufl. |
| Subjects: | |
| Online Access: | Inhaltstext Inhaltsverzeichnis |
| Physical Description: | VIII, 198 S. graph. Darst. |
| ISBN: | 9783869556659 |
Staff View
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Record in the Search Index
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IMAGE 1
CONTENTS
1 INTRODUCTION 1
2 SIGNAL-LIKE PREDICTORS 7
2.1 INTRODUCTION 8
2.2 FEATURE EXTRACTION IN SIGNAL REGRESSION 9
2.2.1 INTRODUCTION 9
2.2.2 FEATURE EXTRACTION AND BLOCKWISE BOOSTING 12
2.2.3 SIMULATION STUDIES 17
2.2.4 EVALUATION BY REAL-WORLD DATA 22
2.2.5 SUMMARY AND DISCUSSION 27
2.3 SUPERVISED FEATURE SELECTION AND CLASSIFICATION IN PROTEOMICS 30
2.3.1 INTRODUCTION 30
2.3.2 METHODS FOR BINARY CLASSIFICATION 31
2.3.3 APPLICATION TO MASS SPECTROMETRY DATA 33
2.3.4 GENERALIZATIONS TO OTHER NON-NORMAL OUTCOMES 36
2.3.5 COMPUTATIONAL ISSUES 38
2.3.6 SUMMARY AND DISCUSSION 40
3 CATEGORICAL PREDICTORS 41
3.1 INTRODUCTION 42
3.2 QUADRATIC REGULARIZATION FOR ORDINAL PREDICTORS 44
3.2.1 INTRODUCTION 44
3.2.2 PENALIZED REGRESSION WITH ORDINAL PREDICTORS 47
3.2.3 SIMULATION STUDIES 51
3.2.4 BIAS-VARIANCE CALCULATIONS 53
3.2.5 APPLICATIONS TO REAL-WORLD DATA 55
3.2.6 HANDLING NON-NORMAL RESPONSES 58
3.2.7 SUMMARY AND DISCUSSION 64
3.2.8 APPENDIX: BIAS, VARIANCES AND AN APPROXIMATE HAT MATRIX . . . 65
3.3 SELECTION OF ORDINALLY SCALED INDEPENDENT VARIABLES 67
3.3.1 INTRODUCTION 67
3.3.2 ORDINAL COVARIATES 69
3.3.3 METHODS PROPOSED 71
3.3.4 APPLICATION TO THE ICF CORE SET FOR CHRONIC WIDESPREAD PAIN . .
76 3.3.5 SUMMARY AND DISCUSSION 81
BIBLIOGRAFISCHE INFORMATIONEN HTTP://D-NB.INFO/1010338188
DIGITALISIERT DURCH
IMAGE 2
VIII CONTENTS
3.3.6 APPENDIX: THE ICF CORE SETS FOR CWP 83
3.4 SPARSE MODELING OF CATEGORICAL EXPLANATORY VARIABLES 87
3.4.1 INTRODUCTION 87
3.4.2 LASSO-TYPE REGULARIZATION FOR CATEGORICAL PREDICTORS 90
3.4.3 NUMERICAL EXPERIMENTS 96
3.4.4 REGULARIZED ANALYSIS OF MUNICH RENT STANDARD DATA 103
3.4.5 SUMMARY AND DISCUSSION 109
3.4.6 APPENDIX: PROPOSITIONS AND PROOFS 110
3.5 REGULARIZATION AND MODEL SELECTION WITH CATEGORICAL EFFECT MODIFIERS
. . . 118 3.5.1 INTRODUCTION 118
3.5.2 PENALIZED ESTIMATION 121
3.5.3 LARGE SAMPLE PROPERTIES AND MODIFICATIONS 124
3.5.4 NUMERICAL EXPERIMENTS 126
3.5.5 REAL WORLD DATA EVALUATION 130
3.5.6 GENERALIZATIONS TO MULTIPLE EFFECT MODIFIERS 134
3.5.7 SUMMARY AND DISCUSSION 136
3.5.8 APPENDIX: DERIVATIONS AND PROOFS 138
3.6 GENERALIZATIONS TO NON-NORMAL OUTCOMES 143
3.6.1 INTRODUCTION 143
3.6.2 PENALIZED LIKELIHOOD ESTIMATION 144
3.6.3 ILLUSTRATIVE EXAMPLES 144
3.6.4 SUMMARY AND DISCUSSION 149
4 NONPARAMETRIC FEATURE EXTRACTION 153
4.1 INTRODUCTION 154
4.2 VARIABLE SCALING AND NEAREST NEIGHBOR METHODS 156
4.2.1 INTRODUCTION 156
4.2.2 SCALING BY POOLED VARIANCES 156
4.2.3 SIMULATION RESULTS 157
4.2.4 SUMMARY AND DISCUSSION 159
4.3 FEATURE SELECTION AND WEIGHTING BY NEAREST NEIGHBOR ENSEMBLES 160
4.3.1 INTRODUCTION 160
4.3.2 NEAREST NEIGHBOR ENSEMBLES 160
4.3.3 SIMULATION STUDIES 165
4.3.4 EVALUATION OF REAL-WORLD DATA 171
4.3.5 HIGH-DIMENSIONAL SETTINGS 175
4.3.6 REGRESSION PROBLEMS 180
4.3.7 SUMMARY AND DISCUSSION 180
4.3.8 APPENDIX: A PROPOSITION ABOUT CLASS-SPECIFIC WEIGHTS 181
5 CONCLUSION AND OUTLOOK 183
REFERENCES 187 |
| any_adam_object | 1 |
| author | Gertheiss, Jan |
| author_facet | Gertheiss, Jan |
| author_role | aut |
| author_sort | Gertheiss, Jan |
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| building | Verbundindex |
| bvnumber | BV037285382 |
| ctrlnum | (OCoLC)711864504 (DE-599)DNB1010338188 |
| dewey-full | 519.5 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5 |
| dewey-search | 519.5 |
| dewey-sort | 3519.5 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| edition | 1. Aufl. |
| format | Thesis Book |
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| isbn | 9783869556659 |
| language | English |
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| physical | VIII, 198 S. graph. Darst. |
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| spelling | Gertheiss, Jan Verfasser aut Feature extraction in regression and classification with structured predictors Jan Gertheiss 1. Aufl. Göttingen Cuvillier 2011 VIII, 198 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Zugl.: München, Univ., Diss., 2010 Zufallsvariable (DE-588)4129514-6 gnd rswk-swf Prädiktor (DE-588)4121498-5 gnd rswk-swf Statistisches Modell (DE-588)4121722-6 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Statistisches Modell (DE-588)4121722-6 s Zufallsvariable (DE-588)4129514-6 s Prädiktor (DE-588)4121498-5 s DE-604 X:MVB text/html http://deposit.dnb.de/cgi-bin/dokserv?id=3678951&prov=M&dok_var=1&dok_ext=htm Inhaltstext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=021198080&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Gertheiss, Jan Feature extraction in regression and classification with structured predictors Zufallsvariable (DE-588)4129514-6 gnd Prädiktor (DE-588)4121498-5 gnd Statistisches Modell (DE-588)4121722-6 gnd |
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| title | Feature extraction in regression and classification with structured predictors |
| title_auth | Feature extraction in regression and classification with structured predictors |
| title_exact_search | Feature extraction in regression and classification with structured predictors |
| title_full | Feature extraction in regression and classification with structured predictors Jan Gertheiss |
| title_fullStr | Feature extraction in regression and classification with structured predictors Jan Gertheiss |
| title_full_unstemmed | Feature extraction in regression and classification with structured predictors Jan Gertheiss |
| title_short | Feature extraction in regression and classification with structured predictors |
| title_sort | feature extraction in regression and classification with structured predictors |
| topic | Zufallsvariable (DE-588)4129514-6 gnd Prädiktor (DE-588)4121498-5 gnd Statistisches Modell (DE-588)4121722-6 gnd |
| topic_facet | Zufallsvariable Prädiktor Statistisches Modell Hochschulschrift |
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