Nitesh V Chawla
Nitesh V Chawla
Frank Freimann Professor of Computer Science & Engg., Notre Dame
Verified email at - Homepage
TitleCited byYear
SMOTE: synthetic minority over-sampling technique
NV Chawla, KW Bowyer, LO Hall, WP Kegelmeyer
Journal of Artificial Intelligence Research (JAIR) 16, 321-357, 2002
Heart disease and stroke statistics: 2006 update
American Heart Association
http://circ. ahajournals. org/cgi/reprint/CIRCULATIONAHA. 105.171600 v1, 2006
Special issue on learning from imbalanced data sets
NV Chawla, N Japkowicz, A Kotcz
ACM Sigkdd Explorations Newsletter 6 (1), 1-6, 2004
SMOTEBoost: Improving prediction of the minority class in boosting
NV Chawla, A Lazarevic, LO Hall, KW Bowyer
European conference on principles of data mining and knowledge discovery …, 2003
Data mining for imbalanced datasets: An overview
NV Chawla
Data mining and knowledge discovery handbook, 875-886, 2009
SVMs modeling for highly imbalanced classification
Y Tang, YQ Zhang, NV Chawla, S Krasser
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 39 …, 2008
New perspectives and methods in link prediction
RN Lichtenwalter, JT Lussier, NV Chawla
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
metapath2vec: Scalable representation learning for heterogeneous networks
Y Dong, NV Chawla, A Swami
Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017
C4. 5 and imbalanced data sets: investigating the effect of sampling method, probabilistic estimate, and decision tree structure
NV Chawla
Proceedings of the ICML 3, 66, 2003
Bringing big data to personalized healthcare: a patient-centered framework
NV Chawla, DA Davis
Journal of general internal medicine 28 (3), 660-665, 2013
A unifying view on dataset shift in classification
JG Moreno-Torres, T Raeder, RO Alaiz-RodríGuez, NV Chawla, F Herrera
Pattern Recognition 45 (1), 521-530, 2012
Learning decision trees for unbalanced data
DA Cieslak, NV Chawla
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2008
When will it happen?: relationship prediction in heterogeneous information networks
Y Sun, J Han, CC Aggarwal, NV Chawla
Proceedings of the fifth ACM international conference on Web search and data …, 2012
Automatically countering imbalance and its empirical relationship to cost
NV Chawla, DA Cieslak, LO Hall, A Joshi
Data Mining and Knowledge Discovery 17 (2), 225-252, 2008
Link prediction and recommendation across heterogeneous social networks
Y Dong, J Tang, S Wu, J Tian, NV Chawla, J Rao, H Cao
2012 IEEE 12th International conference on data mining, 181-190, 2012
Identifying and evaluating community structure in complex networks
K Steinhaeuser, NV Chawla
Pattern Recognition Letters 31 (5), 413-421, 2010
Learning from streaming data with concept drift and imbalance: an overview
TR Hoens, R Polikar, NV Chawla
Progress in Artificial Intelligence 1 (1), 89-101, 2012
Inferring user demographics and social strategies in mobile social networks
Y Dong, Y Yang, J Tang, Y Yang, NV Chawla
Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014
Big data opportunities and challenges: Discussions from data analytics perspectives
ZH Zhou, NV Chawla, Y Jin, GJ Williams
IEEE Computational Intelligence Magazine 9 (4), 62-74, 2014
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
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