William Philip Kegelmeyer
William Philip Kegelmeyer
Verified email at sandia.gov - Homepage
Title
Cited by
Cited by
Year
SMOTE: synthetic minority over-sampling technique
NV Chawla, KW Bowyer, LO Hall, WP Kegelmeyer
Journal of artificial intelligence research 16, 321-357, 2002
123602002
Current status of the digital database for screening mammography
M Heath, K Bowyer, D Kopans, P Kegelmeyer, R Moore, K Chang, ...
Digital mammography, 457-460, 1998
15941998
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
12411997
Data mining: Practical machine learning tools and techniques
HW Ian, F Eibe
Morgan Kaufmann Publishers, 2005
950*2005
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
4702006
Computer-aided mammographic screening for spiculated lesions.
WP Kegelmeyer Jr, JM Pruneda, PD Bourland, A Hillis, MW Riggs, ...
Radiology 191 (2), 331-337, 1994
4381994
Multi-instance multi-label learning
ZH Zhou, ML Zhang, SJ Huang, YF Li
Artificial Intelligence 176 (1), 2291-2320, 2012
3922012
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
3132012
Ensemble diversity measures and their application to thinning
RE Banfield, LO Hall, KW Bowyer, WP Kegelmeyer
Information Fusion 6 (1), 49-62, 2005
2562005
Comparative evaluation of pattern recognition techniques for detection of microcalcifications in mammography
KS Woods, JL Solka, CE Priebe, WP Kegelmeyer Jr, CC Doss, ...
State of The Art in Digital Mammographic Image Analysis, 213-231, 1994
2321994
Comparative evaluation of pattern recognition techniques for detection of microcalcifications in mammography
KS Woods, JL Solka, CE Priebe, WP Kegelmeyer Jr, CC Doss, ...
State of The Art in Digital Mammographic Image Analysis, 213-231, 1994
2321994
Data mining for scientific and engineering applications
RL Grossman, C Kamath, P Kegelmeyer, V Kumar, R Namburu
Springer Science & Business Media, 2013
2242013
Hellinger distance decision trees are robust and skew-insensitive
DA Cieslak, TR Hoens, NV Chawla, WP Kegelmeyer
Data Mining and Knowledge Discovery 24 (1), 136-158, 2012
1802012
Learning ensembles from bites: A scalable and accurate approach
NV Chawla, LO Hall, KW Bowyer, WP Kegelmeyer
Journal of Machine Learning Research 5 (Apr), 421-451, 2004
1652004
A new ensemble diversity measure applied to thinning ensembles
RE Banfield, LO Hall, KW Bowyer, WP Kegelmeyer
International Workshop on Multiple Classifier Systems, 306-316, 2003
972003
Method and apparatus for detecting a desired behavior in digital image data
WP Kegelmeyer Jr
US Patent 5,633,948, 1997
911997
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
832011
Computer detection of stellate lesions in mammograms
WP Kegelmeyer Jr
Biomedical Image Processing and Three-Dimensional Microscopy 1660, 446-454, 1992
821992
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
772003
Evaluation of stellate lesion detection in a standard mammogram data set
WP Kegelmeyer Jr
International Journal of Pattern Recognition and Artificial Intelligence 7 …, 1993
761993
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