SMOTE: synthetic minority over-sampling technique NV Chawla, KW Bowyer, LO Hall, WP Kegelmeyer Journal of artificial intelligence research 16, 321-357, 2002 | 32801 | 2002 |
Current status of the digital database for screening mammography M Heath, K Bowyer, D Kopans, P Kegelmeyer Jr, R Moore, K Chang, ... Digital Mammography: Nijmegen, 1998, 457-460, 1998 | 2329 | 1998 |
Combination of multiple classifiers using local accuracy estimates K Woods, WP Kegelmeyer, K Bowyer IEEE transactions on pattern analysis and machine intelligence 19 (4), 405-410, 1997 | 1449 | 1997 |
Exploring topic coherence over many models and many topics K Stevens, P Kegelmeyer, D Andrzejewski, D Buttler Proceedings of the 2012 joint conference on empirical methods in natural …, 2012 | 794 | 2012 |
A comparison of decision tree ensemble creation techniques RE Banfield, LO Hall, KW Bowyer, WP Kegelmeyer IEEE transactions on pattern analysis and machine intelligence 29 (1), 173-180, 2006 | 633 | 2006 |
Computer-aided mammographic screening for spiculated lesions. WP Kegelmeyer Jr, JM Pruneda, PD Bourland, A Hillis, MW Riggs, ... Radiology 191 (2), 331-337, 1994 | 476 | 1994 |
Hellinger distance decision trees are robust and skew-insensitive DA Cieslak, TR Hoens, NV Chawla, WP Kegelmeyer Data Mining and Knowledge Discovery 24, 136-158, 2012 | 322 | 2012 |
Ensemble diversity measures and their application to thinning RE Banfield, LO Hall, KW Bowyer, WP Kegelmeyer Information Fusion 6 (1), 49-62, 2005 | 311 | 2005 |
Comparative evaluation of pattern recognition techniques for detection of microcalcifications in mammography KS Woods, CC Doss, KW Bowyer, JL Solka, CE Priebe, ... International Journal of Pattern Recognition and Artificial Intelligence 7 …, 1993 | 301 | 1993 |
Data mining for scientific and engineering applications RL Grossman, C Kamath, P Kegelmeyer, V Kumar, R Namburu Springer Science & Business Media, 2013 | 263 | 2013 |
Learning ensembles from bites: A scalable and accurate approach NV Chawla, LO Hall, KW Bowyer, WP Kegelmeyer The Journal of Machine Learning Research 5, 421-451, 2004 | 187 | 2004 |
A new ensemble diversity measure applied to thinning ensembles RE Banfield, LO Hall, KW Bowyer, WP Kegelmeyer Multiple Classifier Systems: 4th International Workshop, MCS 2003 Guildford …, 2003 | 108 | 2003 |
Multilinear algebra for analyzing data with multiple linkages DM Dunlavy, TG Kolda, WP Kegelmeyer Graph algorithms in the language of linear algebra, 85-114, 2011 | 104 | 2011 |
Method and apparatus for detecting a desired behavior in digital image data WP Kegelmeyer Jr US Patent 5,633,948, 1997 | 95 | 1997 |
Computer detection of stellate lesions in mammograms WP Kegelmeyer Jr Biomedical Image Processing and Three-Dimensional Microscopy 1660, 446-454, 1992 | 86 | 1992 |
Distributed learning with bagging-like performance NV Chawla, TE Moore, LO Hall, KW Bowyer, WP Kegelmeyer, C Springer Pattern recognition letters 24 (1-3), 455-471, 2003 | 83 | 2003 |
A comparison of ensemble creation techniques RE Banfield, LO Hall, KW Bowyer, D Bhadoria, WP Kegelmeyer, ... International Workshop on Multiple Classifier Systems, 223-232, 2004 | 77 | 2004 |
The computation of cloud-base height from paired whole-sky imaging cameras MC Allmen, WP Kegelmeyer Jr Journal of Atmospheric and Oceanic Technology 13 (1), 97-113, 1996 | 75 | 1996 |
PostDOCK: a structural, empirical approach to scoring protein ligand complexes C Springer, H Adalsteinsson, MM Young, PW Kegelmeyer, DC Roe Journal of medicinal chemistry 48 (22), 6821-6831, 2005 | 57 | 2005 |
Comet: A recipe for learning and using large ensembles on massive data JD Basilico, MA Munson, TG Kolda, KR Dixon, WP Kegelmeyer 2011 IEEE 11th international conference on data mining, 41-50, 2011 | 51 | 2011 |