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Mining massive e-health data streams for IoMT enabled healthcare systems Journal article
Sensors (Switzerland), 2020,Volume: 20,Issue: 7
Authors:  Toor,Affan Ahmed;  Usman,Muhammad;  Younas,Farah;  Fong,Alvis Cheuk M.;  Khan,Sajid Ali;  Fong,Simon
Favorite |  | TC[WOS]:4 TC[Scopus]:6 | Submit date:2021/03/09
Class imbalance  Concept drift  Data stream mining  Iomt  Machine learning  
Robust Online Multilabel Learning under Dynamic Changes in Data Distribution with Labels Journal article
IEEE Transactions on Cybernetics, 2020,Volume: 50,Issue: 1,Page: 374-385
Authors:  Du,Jie;  Vong,Chi Man
Favorite |  | TC[WOS]:3 TC[Scopus]:4 | Submit date:2021/03/11
Concept drift  dynamic changes  multilabel data streams  online multilabel learning (OMLL)  
Dynamic weighted majority for incremental learning of imbalanced data streams with concept drift? Conference paper
IJCAI International Joint Conference on Artificial Intelligence
Authors:  Lu Y.;  Cheung Y.-M.;  Tang Y.Y.
Favorite |  | TC[WOS]:0 TC[Scopus]:0 | Submit date:2019/02/11
Diversity of Pharmacy Faculty Members between UK and US Journal article
INDIAN JOURNAL OF PHARMACEUTICAL EDUCATION AND RESEARCH, 2017,Volume: 51,Issue: 1,Page: 20-24
Authors:  Zhang, Weixiang;  Wang, Yitao;  Ouyang, Defang
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Diversity  Pharmacy Faculty  Comparison  Us  Uk  
Self-Adaptive Parameters Optimization for Incremental Classification in Big Data Using Neural Network Book chapter
出自: Big Data Applications and Use Cases:Springer, Cham, 2016, 页码: 175-196
Authors:  Fong, Simon;  Fang, Charlie;  Tian, Neal;  Wong, raymond;  Yap, Bee Wah
Favorite |  | TC[WOS]:0 TC[Scopus]:0 | Submit date:2019/07/24
Neural Network  Incremental Machine Learning  Classification  Big Data  Parameter Optimization  
Countering the concept-drift problems in big data by an incrementally optimized stream mining model Journal article
Journal of Systems and Software, 2015,Volume: 102,Page: 158-166
Authors:  Hang Yang;  Simon Fong
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Concept Drift  Data Stream Mining  Very Fast Decision Tree  
Improving the Accuracy of Incremental Decision Tree Learning Algorithm via Loss Function Conference paper
Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013, Sydney, NSW, Australia, 3-5 Dec. 2013
Authors:  Hang Yang;  Simon Fong
Favorite |  | TC[WOS]:3 TC[Scopus]:4 | Submit date:2019/02/13
Data Stream Mining  Decision Tree Classification  Hoeffding Tree  
Countering the Concept-drift Problem in Big Data Using iOVFDT Conference paper
Proceedings - 2013 IEEE International Congress on Big Data, BigData 2013, Santa Clara, CA, USA, 27 June-2 July 2013
Authors:  Hang Yang;  Simon Fong
Favorite |  | TC[WOS]:10 TC[Scopus]:11 | Submit date:2019/02/13
Classification  Concept Drift  Data Stream Mining  Incremental Decision Tree  
Improving the accuracy of incremental decision tree learning algorithm via loss function Conference paper
Proceedings - 16th IEEE International Conference on Computational Science and Engineering, CSE 2013
Authors:  Yang,Hang;  Fong,Simon
Favorite |  | TC[WOS]:3 TC[Scopus]:4 | Submit date:2021/03/09
Data Stream Mining  Decision Tree Classification  Hoeffding Tree  
Countering the concept-drift problem in big data using iOVFDT Conference paper
Proceedings - 2013 IEEE International Congress on Big Data, BigData 2013
Authors:  Yang,Hang;  Fong,Simon
Favorite |  | TC[WOS]:10 TC[Scopus]:11 | Submit date:2021/03/09
classification  concept drift  data stream mining  incremental decision tree