Kai Ming Ting

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Zhi-Hua ZhouNanjing UniversityVerified email at nju.edu.cn
Ye ZhuSenior Lecturer of Computer Science, Deakin UniversityVerified email at deakin.edu.au
Geoff WebbProfessor, Department of Data Science and Artificial Intelligence, Monash UniversityVerified email at monash.edu
Swee Chuan TanAssociate Professor, Singapore University of Social SciencesVerified email at suss.edu.sg
Sunil Aryal, PhD, FHEADeakin University AustraliaVerified email at deakin.edu.au
Guojun LuFederation University AustraliaVerified email at federation.edu.au
Dengsheng ZhangFederation University AustraliaVerified email at federation.edu.au
Ian H. WittenProfessor of Computer Science, University of Waikato, New ZealandVerified email at waikato.ac.nz
Zhouyu FuLead Researcher, Microsoft Research AsiaVerified email at microsoft.com
Shyh Wei TengFederation University Australia - Institute of Innovation, Science & SustainabilityVerified email at federation.edu.au
Mark J. CarmanAssociate Professor, DEIB, Politecnico di MilanoVerified email at polimi.it
Gholamreza (Reza) HaffariProfessor and ARC Future Fellow, DSAI Dept, Monash UniversityVerified email at monash.edu
Guang-Tong ZhouFacebookVerified email at fb.com
Tharindu BandaragodaResearch Centre for Data Analytics & Cognition, La Trobe UniversityVerified email at latrobe.edu.au
Guansong PangAssistant Professor of Computer Science, Singapore Management UniversityVerified email at smu.edu.sg
Xin MuPeng Cheng LaboratoryVerified email at lamda.nju.edu.cn
Yang YuProfessor, Nanjing UniversityVerified email at nju.edu.cn
Kevin B KorbHonorary Senior Fellow, University of Melbourne
Bo ChenSeeing MachinesVerified email at seeingmachines.com

Kai Ming Ting

Nanjing University

Verified email at nju.edu.cn - Homepage

Machine Learning Data Mining


Title Sort by citations Sort by year Sort by 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	6583	2008
Isolation-based anomaly detection FT Liu, KM Ting, ZH Zhou ACM Transactions on Knowledge Discovery from Data (TKDD) 6 (1), 1-39, 2012	2076	2012
Issues in stacked generalization KM Ting, IH Witten Journal of artificial intelligence research 10, 271-289, 1999	936	1999
Confusion matrix KM Ting Encyclopedia of machine learning, 209-209, 2011	699	2011
An instance-weighting method to induce cost-sensitive trees KM Ting IEEE Transactions on Knowledge and Data Engineering 14 (3), 659-665, 2002	642	2002
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	619	2010
A comparative study of cost-sensitive boosting algorithms KM Ting Proceedings of the seventeenth international conference on machine learning …, 2000	400	2000
Fast anomaly detection for streaming data SC Tan, KM Ting, TF Liu Twenty-second international joint conference on artificial intelligence, 2011	369	2011
Stacking bagged and dagged models KM Ting, IH Witten	339	1997
Precision and Recall. KM Ting Encyclopedia of machine learning 781, 2010	327	2010
Stacked Generalization: when does it work? KM Ting, IH Witten Department of Computer Science, University of Waik, 1997	267	1997
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	210	2006
On detecting clustered anomalies using sciforest FT Liu, KM Ting, ZH Zhou Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010	184	2010
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	153	2018
Inducing cost-sensitive trees via instance weighting KM Ting European symposium on principles of data mining and knowledge discovery, 139-147, 1998	146	1998
Density-ratio based clustering for discovering clusters with varying densities Y Zhu, KM Ting, MJ Carman Pattern Recognition 60, 983-997, 2016	143	2016
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	130	2017
On the application of ROC analysis to predict classification performance under varying class distributions GI Webb, KM Ting Machine learning 58, 25-32, 2005	126	2005
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	122	2012
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	111	2018

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