KNN-AdaBoost 모델과 AdaBoost-SVM 모델을 통한 준교사학습 비교

• 영문명: semi-supervised Learning compared with KNN-AdaBoost model and AdaBoost-SVM model
• 발행기관: 한국IT마케팅학회
• 저자명: 유회중(Hoe Joong You) 권영만(Young Man Kwon)
• 간행물 정보: 『한국IT마케팅학회 논문집』한국IT마케팅학회 논문집 1권 1호, 74~75쪽, 전체 2쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2014.11.27

영문 초록

The supervised-learning and unsupervised-learning when analyzed in the case of the one without as there are output information is combined data, the error rate is not easily trust that a comparison learning history. Therefore I suggest the semi-supervised- learning that gave me that were mixed compared to history unsupervised-learning and supervised-learning. In addition, the semi-supervised learning that gave are mutually comparing model that combines the model and AdaBoost and SVM bound the KNN algorithm and AdaBoost algorithm, to check the semi-supervised learning of the error rate is low binding model.

목차

Abstract

Ⅰ. 서론

Ⅱ. 관련연구

Ⅲ. 모의실험

Ⅳ. 결론

참고문헌

키워드

KNN SVM AdaBoost semi-supervised-learning supervised-learning unsupervised-learning