A New Scalable and Performance-Enhancing Bootstrap Aggregating Scheme for Variables Selection - Taking Real-World Web Services Resources as a Case

Variables selection is a vital Data Mining technique which is used to select the cost-effective predictors by discarding variables with little or no predictive power.

[1]  Dunja Mladenic,et al.  Feature selection on hierarchy of web documents , 2003, Decis. Support Syst..

[2]  M. Punithavalli,et al.  An E-SMOTE technique for feature selection in High-Dimensional Imbalanced Dataset , 2011, 2011 3rd International Conference on Electronics Computer Technology.

[3]  Hua Li,et al.  The study on technologies for feature selection , 2002, Proceedings. International Conference on Machine Learning and Cybernetics.

[4]  Nasser Yazdani,et al.  Mutual information-based feature selection for intrusion detection systems , 2011, J. Netw. Comput. Appl..

[5]  Du-Ming Tsai,et al.  Automatic defect inspection for LCDs using singular value decomposition , 2005 .

[6]  Martin Grootveld,et al.  Self Organising Maps for variable selection: Application to human saliva analysed by nuclear magnetic resonance spectroscopy to investigate the effect of an oral healthcare product , 2009 .

[7]  David S. Wishart,et al.  MetaboAnalyst: a web server for metabolomic data analysis and interpretation , 2009, Nucleic Acids Res..

[8]  Rong Jin,et al.  Online feature selection for mining big data , 2012, BigMine '12.

[9]  D Gianola,et al.  Dimension reduction and variable selection for genomic selection: application to predicting milk yield in Holsteins. , 2011, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

[10]  Kazuyuki Murase,et al.  A new wrapper feature selection approach using neural network , 2010, Neurocomputing.

[11]  Yi Liu,et al.  FS_SFS: A novel feature selection method for support vector machines , 2006, Pattern Recognit..

[12]  Inderveer Chana,et al.  Cloud based intelligent system for delivering health care as a service , 2014, Comput. Methods Programs Biomed..

[13]  Chih-Jen Lin,et al.  Projected Gradient Methods for Nonnegative Matrix Factorization , 2007, Neural Computation.

[14]  Ferat Sahin,et al.  A survey on feature selection methods , 2014, Comput. Electr. Eng..

[15]  Ana Azevedo.  Integration of Data Mining in Business Intelligence Systems , 2014 .

[16]  Anongnart Srivihok,et al.  Wrapper Feature Subset Selection for Dimension Reduction Based on Ensemble Learning Algorithm , 2015 .

[17]  L. Fahrmeir,et al.  Spatial Bayesian Variable Selection With Application to Functional Magnetic Resonance Imaging , 2007 .

[18]  Nikola Bogunovic,et al.  A review of feature selection methods with applications , 2015, 2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).

[19]  Kazuyuki Murase,et al.  A new hybrid ant colony optimization algorithm for feature selection , 2012, Expert Syst. Appl..

[20]  Haesun Park,et al.  Sparse Nonnegative Matrix Factorization for Clustering , 2008 .

[21]  Wenke Lee,et al.  Intrusion Detection Techniques for Mobile Wireless Networks , 2003, Wirel. Networks.

[22]  James A. Landay,et al.  The Mobile Sensing Platform: An Embedded Activity Recognition System , 2008, IEEE Pervasive Computing.