A bagging SVM to learn from positive and unlabeled examples
Top Cited Papers
- 1 February 2014
- journal article
- research article
- Published by Elsevier BV in Pattern Recognition Letters
- Vol. 37, 201-209
- https://doi.org/10.1016/j.patrec.2013.06.010
Abstract
No abstract availableKeywords
This publication has 14 references indexed in Scilit:
- LIBSVMACM Transactions on Intelligent Systems and Technology, 2011
- SVM-HUSTLE—an iterative semi-supervised machine learning approach for pairwise protein remote homology detectionBioinformatics, 2008
- Many Microbe Microarrays Database: uniformly normalized Affymetrix compendia with structured experimental metadataNucleic Acids Research, 2007
- Kernel-based data fusion for gene prioritizationBioinformatics, 2007
- Gene prioritization through genomic data fusionNature Biotechnology, 2006
- Learning from positive and unlabeled examplesTheoretical Computer Science, 2005
- A Neyman–Pearson Approach to Statistical LearningIEEE Transactions on Information Theory, 2005
- Pebl:web page classification without negative examplesIEEE Transactions on Knowledge and Data Engineering, 2004
- Estimating the Support of a High-Dimensional DistributionNeural Computation, 2001
- Bagging predictorsMachine Learning, 1996