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Feature Selection Methods: Case of Filter and Wrapper Approaches for Maximising Classification Accuracy Journal article
Yap Bee Wah, Nurain Ibrahim, Hamzah Abdul Hamid, Shuzlina Abdul-Rahman, Simon Fong. Feature Selection Methods: Case of Filter and Wrapper Approaches for Maximising Classification Accuracy[J]. Pertanika Journal of Science and Technology, 2018, 26(1), 329-340.
Authors:  Yap Bee Wah;  Nurain Ibrahim;  Hamzah Abdul Hamid;  Shuzlina Abdul-Rahman;  Simon Fong
Favorite | TC[WOS]:77 TC[Scopus]:127  IF:0.6/0.6 | Submit date：2019/02/13
Feature Selection Methods  Filter Method  Logistic Regression  Simulation  Wrapper Method  
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]:7 TC[Scopus]:0 | Submit date：2019/07/24
Neural Network  Incremental Machine Learning  Classification  Big Data  Parameter Optimization  
A Lightweight Data Preprocessing Strategy with Fast Contradiction Analysis for Incremental Classifier Learning Journal article
Simon Fong, Robert P. Biuk-Aghai, Yain-whar Si, Bee Wah Yap. A Lightweight Data Preprocessing Strategy with Fast Contradiction Analysis for Incremental Classifier Learning[J]. Mathematical Problems in Engineering, 2015, 2015.
Authors:  Simon Fong;  Robert P. Biuk-Aghai;  Yain-whar Si;  Bee Wah Yap
Favorite | TC[WOS]:2 TC[Scopus]:5  IF:1.430/1.393 | Submit date：2019/02/13
Incremental Learning Algorithms for Fast Classification in Data Stream Conference paper
Simon Fong, Zhicong Luo, Bee Wah Yap. Incremental Learning Algorithms for Fast Classification in Data Stream[C]:IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA, 2014, 186-190.
Authors:  Simon Fong;  Zhicong Luo;  Bee Wah Yap
Favorite | TC[WOS]:1 TC[Scopus]:5 | Submit date：2019/02/13
Data Mining  Classification  Oulier Dectction  Lightweight  Incremental Learning  
Incremental Methods for Detecting Outliers from Multivariate Data Stream Conference paper
Simon Fong, Zhicong Luo, Bee Wah Yap, Suash Deb. Incremental Methods for Detecting Outliers from Multivariate Data Stream[C], 2014, 369-377.
Authors:  Simon Fong;  Zhicong Luo;  Bee Wah Yap;  Suash Deb
Favorite | TC[Scopus]:3 | Submit date：2019/02/13
Data Stream Mining  Incremental Processing  Outlier Detection  
An Application of Oversampling, Undersampling, Bagging and Boosting in Handling Imbalanced Datasets Conference paper
Bee Wah Yap, Khatijahhusna Abd Rani, Hezlin Aryani Abd Rahman, Simon Fong, Zuraida Khairudin, Nik Nik Abdullah. An Application of Oversampling, Undersampling, Bagging and Boosting in Handling Imbalanced Datasets[C], 2014, 13-22.
Authors:  Bee Wah Yap;  Khatijahhusna Abd Rani;  Hezlin Aryani Abd Rahman;  Simon Fong;  Zuraida Khairudin; et al.
Favorite | TC[Scopus]:188 | Submit date：2019/02/13
Bagging  Boosting  Imbalanced Data  Oversampling  Undersampling  
A Prediction Model for Forecasting the Trend of Macau Property Price Movements and Understanding the Influential Factors Journal article
Simon Fong, Yap Bee Wah. A Prediction Model for Forecasting the Trend of Macau Property Price Movements and Understanding the Influential Factors[J]. Journal of Emerging Technologies in Web Intelligence, 2013, 5(2), 122-131.
Authors:  Simon Fong;  Yap Bee Wah
Favorite | TC[Scopus]:2 | Submit date：2019/02/13
Data Mining  Svm  Neural Network  c&r Tree  Weka  Spss  Multilayer Perception Model  
Predicting car purchase intent using data mining approach Conference paper
Yap Bee Wah, Nor Huwaina Ismail, Simon Fong. Predicting car purchase intent using data mining approach[C], 2011, 1994-1999.
Authors:  Yap Bee Wah;  Nor Huwaina Ismail;  Simon Fong
Favorite | TC[Scopus]:6 | Submit date：2019/02/13
Classification  Data Mining  Decision Tree  Logistic Regression  Predictive Modeling