Kai Ming Ting
Kai Ming Ting
Verified email at nju.edu.cn - Homepage
Title
Cited by
Cited by
Year
Isolation forest
FT Liu, KM Ting, ZH Zhou
2008 eighth ieee international conference on data mining, 413-422, 2008
20482008
Isolation-based anomaly detection
FT Liu, KM Ting, ZH Zhou
ACM Transactions on Knowledge Discovery from Data (TKDD) 6 (1), 1-39, 2012
7972012
Issues in stacked generalization
KM Ting, IH Witten
Journal of artificial intelligence research 10, 271-289, 1999
7281999
An instance-weighting method to induce cost-sensitive trees
KM Ting
IEEE Transactions on Knowledge and Data Engineering 14 (3), 659-665, 2002
5032002
A survey of audio-based music classification and annotation
Z Fu, G Lu, KM Ting, D Zhang
IEEE transactions on multimedia 13 (2), 303-319, 2010
4652010
A comparative study of cost-sensitive boosting algorithms
KM Ting
In Proceedings of the 17th International Conference on Machine Learning, 2000
3352000
Stacking bagged and dagged models
KM Ting, IH Witten
2521997
Confusion matrix.
KM Ting, C Sammut, GI Webb
Encyclopedia of Machine Learning and Data Mining 260, 2017
2392017
Stacked Generalization: when does it work?
KM Ting, IH Witten
Department of Computer Science, University of Waik, 1997
1961997
Fast anomaly detection for streaming data
SC Tan, KM Ting, TF Liu
Twenty-Second International Joint Conference on Artificial Intelligence, 2011
1682011
Precision and recall
KM Ting
Encyclopedia of machine learning, 781-781, 2011
1662011
z-SVM: An SVM for improved classification of imbalanced data
T Imam, KM Ting, J Kamruzzaman
Australasian Joint Conference on Artificial Intelligence, 264-273, 2006
1512006
Inducing cost-sensitive trees via instance weighting
KM Ting
European symposium on principles of data mining and knowledge discovery, 139-147, 1998
1211998
On the application of ROC analysis to predict classification performance under varying class distributions
GI Webb, KM Ting
Machine learning 58 (1), 25-32, 2005
1082005
Learning by extrapolation from marginal to full-multivariate probability distributions: decreasingly naive Bayesian classification
GI Webb, JR Boughton, F Zheng, KM Ting, H Salem
Machine learning 86 (2), 233-272, 2012
1072012
On detecting clustered anomalies using SCiForest
FT Liu, KM Ting, ZH Zhou
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2010
952010
The problem of small disjuncts: its remedy in decision trees
KM Ting
PROCEEDINGS OF THE BIENNIAL CONFERENCE-CANADIAN SOCIETY FOR COMPUTATIONAL …, 1994
911994
Density-ratio based clustering for discovering clusters with varying densities
Y Zhu, KM Ting, MJ Carman
Pattern Recognition 60, 983-997, 2016
792016
Spectrum of variable-random trees
FT Liu, KM Ting, Y Yu, ZH Zhou
Journal of Artificial Intelligence Research 32, 355-384, 2008
752008
Classification under streaming emerging new classes: A solution using completely-random trees
X Mu, KM Ting, ZH Zhou
IEEE Transactions on Knowledge and Data Engineering 29 (8), 1605-1618, 2017
672017
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Articles 1–20