Követés
Kai Ming Ting
Kai Ming Ting
Nanjing University
E-mail megerősítve itt: nju.edu.cn - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Isolation forest
FT Liu, KM Ting, ZH Zhou
2008 eighth ieee international conference on data mining, 413-422, 2008
65882008
Isolation-based anomaly detection
FT Liu, KM Ting, ZH Zhou
ACM Transactions on Knowledge Discovery from Data (TKDD) 6 (1), 1-39, 2012
20762012
Issues in stacked generalization
KM Ting, IH Witten
Journal of artificial intelligence research 10, 271-289, 1999
9361999
Confusion matrix
KM Ting
Encyclopedia of machine learning, 209-209, 2011
7012011
An instance-weighting method to induce cost-sensitive trees
KM Ting
IEEE Transactions on Knowledge and Data Engineering 14 (3), 659-665, 2002
6422002
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
6192010
A comparative study of cost-sensitive boosting algorithms
KM Ting
Proceedings of the seventeenth international conference on machine learning …, 2000
3992000
Fast anomaly detection for streaming data
SC Tan, KM Ting, TF Liu
Twenty-second international joint conference on artificial intelligence, 2011
3692011
Stacking bagged and dagged models
KM Ting, IH Witten
3401997
Precision and Recall.
KM Ting
Encyclopedia of machine learning 781, 2010
3272010
Stacked Generalization: when does it work?
KM Ting, IH Witten
Department of Computer Science, University of Waik, 1997
2671997
z-SVM: An SVM for improved classification of imbalanced data
T Imam, KM Ting, J Kamruzzaman
AI 2006: Advances in Artificial Intelligence: 19th Australian Joint …, 2006
2102006
On detecting clustered anomalies using sciforest
FT Liu, KM Ting, ZH Zhou
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010
1842010
Isolation‐based anomaly detection using nearest‐neighbor ensembles
TR Bandaragoda, KM Ting, D Albrecht, FT Liu, Y Zhu, JR Wells
Computational Intelligence 34 (4), 968-998, 2018
1532018
Inducing cost-sensitive trees via instance weighting
KM Ting
European symposium on principles of data mining and knowledge discovery, 139-147, 1998
1461998
Density-ratio based clustering for discovering clusters with varying densities
Y Zhu, KM Ting, MJ Carman
Pattern Recognition 60, 983-997, 2016
1432016
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
1302017
On the application of ROC analysis to predict classification performance under varying class distributions
GI Webb, KM Ting
Machine learning 58, 25-32, 2005
1262005
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, 233-272, 2012
1222012
Multi-label learning with emerging new labels
Y Zhu, KM Ting, ZH Zhou
IEEE Transactions on Knowledge and Data Engineering 30 (10), 1901-1914, 2018
1112018
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