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Multi-Class SVM+MTL for the Prediction of Corporate Credit Rating with Structured Data
저자
임강, 홍태호, YoungKi Park
학술지명
Asia Pacific Journal of Information Systems
출판/발행연도
2015
주제
요약
본 연구는 구조화된 데이터를 활용하여 기업 신용 등급 예측에 SVM+ 및 SVM+MTL과 같은 새로운 기법을 적용하고, 기존 SVM과의 예측 성능을 비교합니다. 실험 결과, SVM+MTL이 기존 SVM 및 SVM+보다 우수한 예측 성능을 보였으며, 다중 분류 문제 해결 기법을 풍부하게 하는 데 기여합니다.
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