Double-bagging: combining classifiers by bootstrap aggregation
- 30 June 2003
- journal article
- Published by Elsevier in Pattern Recognition
- Vol. 36 (6) , 1303-1309
- https://doi.org/10.1016/s0031-3203(02)00169-3
Abstract
No abstract availableKeywords
This publication has 17 references indexed in Scilit:
- Dynamic classifier selection based on multiple classifier behaviourPattern Recognition, 2001
- A direct LDA algorithm for high-dimensional data — with application to face recognitionPublished by Elsevier ,2001
- A statistical unified framework for rank-based multiple classifier decision combinationPattern Recognition, 2001
- Decision templates for multiple classifier fusion: an experimental comparisonPattern Recognition, 2001
- A linear constrained distance-based discriminant analysis for hyperspectral image classificationPattern Recognition, 2001
- Boosting the margin: a new explanation for the effectiveness of voting methodsThe Annals of Statistics, 1998
- Bagging for linear classifiersPattern Recognition, 1998
- Improvements on Cross-Validation: The .632+ Bootstrap MethodJournal of the American Statistical Association, 1997
- Combining Estiamates in Regression and ClassificationJournal of the American Statistical Association, 1996
- R: A Language for Data Analysis and GraphicsJournal of Computational and Graphical Statistics, 1996