UBoost: A boosting method for producing uniform selection efficiencies from multivariate classifiers

Journal of Instrumentation

Volumn 8, Issue 12, 2013, Pages

  Stevens, J ^a   Williams, M ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Analysis and statistical methods; Data processing methods

Indexed keywords

AMPLITUDE ANALYSIS; BOOSTING METHOD; DATA PROCESSING METHODS; FIGURE OF MERITS;

DATA PROCESSING;

DECISION TREES;

EID: 84892849059     PISSN: None     EISSN: 17480221     Source Type: Journal    
DOI: 10.1088/1748-0221/8/12/P12013     Document Type: Article

References (7)

1. L. Brieman et al. 1984 Classification and regression trees, Wadsworth International Group, Belmont U.S.A.
2. LHCb Trigger Group, R. Aaij et al. 2013 The LHCb trigger and its performance, JINST 8 P04022 [arXiv:1211.3055]
3. V. Gligorov and M. Williams 2013 Efficient, reliable and fast high-level triggering using a bonsai boosted decision tree, JINST 8 P02013 [arXiv:1210.6861]
4. Y. Freund and R.E. Schapire 1997 A decision-theoretic generalization of on-line learning and an application to boosting, J. Comput. System Sci. 55 119
5. J.L. Bentley 1975 Multidimensional binary search trees used for associative searching, Commun. ACM 18 509
6. A. Hoecker et al. TMVA: Toolkit for Multivariate Data Analysis, PoS(ACAT)040 [physics/0703039]
7. L. Breiman 1996 Bagging predictors, Mach. Learn. 24 123