Nitesh V Chawla
Nitesh V Chawla
Frank Freimann Professor of Computer Science & Engg., Notre Dame
Verified email at - Homepage
Cited by
Cited by
SMOTE: synthetic minority over-sampling technique
NV Chawla, KW Bowyer, LO Hall, WP Kegelmeyer
Journal of Artificial Intelligence Research (JAIR) 16, 321-357, 2002
Data mining and knowledge discovery handbook
O Maimon, L Rokach
Springer 2 (2005), 2005
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
metapath2vec: Scalable representation learning for heterogeneous networks
Y Dong, NV Chawla, A Swami
Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017
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
A unifying view on dataset shift in classification
JG Moreno-Torres, T Raeder, R Alaiz-Rodríguez, NV Chawla, F Herrera
Pattern recognition 45 (1), 521-530, 2012
SMOTE for learning from imbalanced data: progress and challenges, marking the 15-year anniversary
A Fernández, S Garcia, F Herrera, NV Chawla
Journal of artificial intelligence research 61, 863-905, 2018
Bringing big data to personalized healthcare: a patient-centered framework
NV Chawla, DA Davis
Journal of general internal medicine 28 (3), 660-665, 2013
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
Learning decision trees for unbalanced data
DA Cieslak, NV Chawla
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2008
Heterogeneous graph neural network
C Zhang, D Song, C Huang, A Swami, NV Chawla
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
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
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
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
Big data opportunities and challenges: Discussions from data analytics perspectives [discussion forum]
ZH Zhou, NV Chawla, Y Jin, GJ Williams
IEEE Computational intelligence magazine 9 (4), 62-74, 2014
Combating imbalance in network intrusion datasets.
DA Cieslak, NV Chawla, A Striegel
GrC, 732-737, 2006
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