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Machine learning feature selection of financial data : 기계학습의 변수선별법을 통한 금융데이터 분석
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 최형인 | - |
dc.contributor.author | 김시연 | - |
dc.date.accessioned | 2017-07-19T09:00:38Z | - |
dc.date.available | 2017-07-19T09:00:38Z | - |
dc.date.issued | 2015-02 | - |
dc.identifier.other | 000000025554 | - |
dc.identifier.uri | https://hdl.handle.net/10371/131496 | - |
dc.description | 학위논문 (석사)-- 서울대학교 대학원 : 수리과학부, 2015. 2. 최형인. | - |
dc.description.abstract | Global financial crisis has been occurred frequently in these days also na-
tions and companies pay attention to predict bankruptcy. In this thesis, we discuss feature selection method to extract feature group that causes main factors of making bankruptcy. We describe stepwise method and principal component analysis method briefl y and compare it to construct prediction model. In addition, we try to analyze their performance and statistical mea- surement which method is the most efficient to raw data. We deal with data set of experiments which consist of 515 companies' financial statement in 1997 to build the model by using support vector machine. | - |
dc.description.tableofcontents | Abstract i
1 Introduction 1 2 Feature Selection Method 3 2.1 Stepwise method . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2 Principal component analysis . . . . . . . . . . . . . . . . . . 5 3 Data and experiment 10 3.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.2 Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 4 Result 14 4.1 Stepwise method . . . . . . . . . . . . . . . . . . . . . . . . . 14 4.2 Principal component analysis . . . . . . . . . . . . . . . . . . 15 4.3 Comparing feature selection . . . . . . . . . . . . . . . . . . . 16 5 Conclusion 20 Abstract (in Korean) 22 | - |
dc.format | application/pdf | - |
dc.format.extent | 3170658 bytes | - |
dc.format.medium | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | 서울대학교 대학원 | - |
dc.subject | feature selection | - |
dc.subject | stepwise | - |
dc.subject | principal component analysis | - |
dc.subject | bankruptcy prediction | - |
dc.subject.ddc | 510 | - |
dc.title | Machine learning feature selection of financial data | - |
dc.title.alternative | 기계학습의 변수선별법을 통한 금융데이터 분석 | - |
dc.type | Thesis | - |
dc.contributor.AlternativeAuthor | Kim Shi Yeon | - |
dc.description.degree | Master | - |
dc.citation.pages | ii,23 | - |
dc.contributor.affiliation | 자연과학대학 수리과학부 | - |
dc.date.awarded | 2015-02 | - |
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