지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2013.4
- 수록면
- 166 - 171 (6page)
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초록· 키워드
오류제보하기
The method proposed in this paper can improve the performance of the Boosting algorithm in machine learning. The proposed Boundary AdaBoost algorithm can make up for the weak points of Normal binary classifier using threshold boundary concepts. The new proposed boundary can be located near the threshold of the binary classifier. The proposed algorithm improves classification in areas where Normal binary classifier is weak. Thus, the optimal boundary final classifier can decrease error rates classified with more reasonable features. Finally, this paper derives the new algorithm’s optimal solution, and it demonstrates how classifier accuracy can be improved using the proposed Boundary AdaBoost in a simulation experiment of pedestrian detection using 10-fold cross validation.
목차
Abstract
1. Introduction
2. Background
3. Boundary AdaBoost
4. Experimental Classification Results
5. Conclusions
References
참고문헌 (19)
참고문헌 신청
1. [학술지(정기간행물)] - Y. Freund / 1999 / A Short Introduction to Boosting / Journal of Japanese Society for Artificial Intelligence 14 (5) : 771 ~ 780
2. [학술지(정기간행물)] - R. E. Schapire / 1999 / Improved Boosting Algorithms Using Confidence-rated Predictions / Machine Learning 37 (3) : 297 ~ 335
3. [학술지(정기간행물)] - J. Friedman / 2000 / Additive Logistic Regression : a Statistical View of Boosting / The Annals of Statistics 28 (2) : 337 ~ 407
4. [단행본] - A. Vezhnevets / 2005 / Modest AdaBoost-Teaching AdaBoost to Generalize Better / Graphicon
5. [학술대회논문] - R. E. Schapire / 1999 / Theoretical Views of Boosting and Applications / Proceedings of Algorithmic Learning Theory 1720 : 13 ~ 25
2. [학술지(정기간행물)] - R. E. Schapire / 1999 / Improved Boosting Algorithms Using Confidence-rated Predictions / Machine Learning 37 (3) : 297 ~ 335
3. [학술지(정기간행물)] - J. Friedman / 2000 / Additive Logistic Regression : a Statistical View of Boosting / The Annals of Statistics 28 (2) : 337 ~ 407
4. [단행본] - A. Vezhnevets / 2005 / Modest AdaBoost-Teaching AdaBoost to Generalize Better / Graphicon
5. [학술대회논문] - R. E. Schapire / 1999 / Theoretical Views of Boosting and Applications / Proceedings of Algorithmic Learning Theory 1720 : 13 ~ 25
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UCI(KEPA) : I410-ECN-0101-2014-020-002620807