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Fayyad U, Piatetsky-Shapiro G, Smyth P. From Data Mining to Knowledge Discovery in Databases, AI Magazine, vol.17, pp. 37-24, 1996.10.1145/240455.240463Search in Google Scholar
Langley P. Selection of relevant features in machine learning, Proc of the AAAI Fall Symposium on Relevance, Menlo Park, pp.140-144, 1994.10.21236/ADA292575Search in Google Scholar
Song Q, Ni J, Wang G. A fast clustering-based feature subset selection algorithm for highdimensional data, Knowledge and Data Engineering, IEEE Transactions on, vol.25, no.1, pp.1-14, 2013.10.1109/TKDE.2011.181Search in Google Scholar
Lopez M I, Luna J M, Romero C, et al. Classification via Clustering for Predicting Final Marks Based on Student Participation in Forums, 5th International Conference on Educational Data Mining, pp. 148-151, 2012.Search in Google Scholar
Kira K, Rendell L. A practical approach to feature selection, Proc of the 9th International Conference on Machine Learning, pp. 249-256, 1992.10.1016/B978-1-55860-247-2.50037-1Search in Google Scholar
Dash M, Liu H. Consistency-based search in feature selection, Artificial Intelligence, vol. 151, no.1-2, pp. 155-176, 2003.10.1016/S0004-3702(03)00079-1Search in Google Scholar
Wei H-L, Billings S A. Feature Subset Selection and Ranking for Data Dimensionality Reduction, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.29, no1. 162-166, 2007.10.1109/TPAMI.2007.25060717108391Search in Google Scholar
Yin L, Ge Y, Xiao K, et al. Feature selection for high-dimensional imbalanced data, Neurocomputing, vol. 105, pp. 3-11, 2013.10.1016/j.neucom.2012.04.039Search in Google Scholar
Li B Q, Hu L L, Chen L, et al, Prediction of protein domain with mRMR feature selection and analysis, PLoS One, 2012, 7(6): http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039308.10.1371/journal.pone.0039308337612422720092Search in Google Scholar
Peng H, Long F, Ding C. Feature Selection Based on Mutual Information: Criteria of MaxDependency, Max-Relevance, and Min-Redundancy, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.27, no.8, pp. 1226-1238, 2005.Search in Google Scholar
Foithong S, Pinngern O, Attachoo B. Feature subset selection wrapper based on mutual information and rough sets, Expert Systems with Applications, vol.39, no.1, pp. 574-584, 2012.10.1016/j.eswa.2011.07.048Search in Google Scholar
Guyon I, Weston J, Barnhill S, et al. Gene selection for cancer classification using support vector machines, Machine Learning, vol.46, no.1-3, pp.389-422, 2002.10.1023/A:1012487302797Search in Google Scholar
Suzuki T, Sugiyama M. Sufficient dimension reduction via squared-loss mutual information estimation, Neural computation, vol.25, no.3, pp. 725-758, 2013.10.1162/NECO_a_0040723272920Search in Google Scholar
Das S. Filters, Wrappers and a Boosting-Based Hybrid for Feature Selection, Proc of the 18th International Conference on Machine Learning, San Francisco, CA, USA, pp. 74-81, 2001.Search in Google Scholar
Li G-Z, Meng H-H, Lu W-C, et al. Asymmetric bagging and feature selection for activities prediction of drug molecules, BMC Bioinformatics, vol.9, no.S6, pp. 7-11, 2008.10.1186/1471-2105-9-S6-S7242344818541060Search in Google Scholar
Huang D, Chow T W S. Effective feature selection scheme using mutual information, Neurocomputing, vol.63, pp. 325-343, 2005.10.1016/j.neucom.2004.01.194Search in Google Scholar
Jain A K, Duin R P W, Mao J. Statistical Pattern Recognition: A Review, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.22, no.1, pp. 4 – 37, 2000.10.1109/34.824819Search in Google Scholar
N. K. Suryadevara and S. C. Mukhopadhyay, “Determining Wellness Through An Ambient Assisted Living Environment”, IEEE Intelligent Systems, May/June 2014, pp. 30-37.10.1109/MIS.2014.16Search in Google Scholar
Foithong S, Pinngern O, Attachoo B. Feature subset selection wrapper based on mutual information and rough sets, Expert Systems with Applications, vol.39, no.1, pp. 574-584, 2012.10.1016/j.eswa.2011.07.048Search in Google Scholar
N. K. Suryadevara, S. C. Mukhopadhyay, R.Wang, R.K. Rayudu and Y. M. Huang, Reliable Measurement of Wireless Sensor Network Data for Forecasting Wellness of Elderly at Smart Home, Proceedings of IEEE I2MTC 2013 conference, IEEE Catalog number CFP13IMT-CDR, ISBN 978-14673-4622-1, May 6-9, 2013, Minneapolis, USA, pp. 16-21.10.1109/I2MTC.2013.6555372Search in Google Scholar
Ang K K, Chin Z Y, Zhang H, et al. Mutual information-based selection of optimal spatial–temporal patterns for single-trial EEG-based BCIs, Pattern Recognition, vol.45, no.6, pp. 2137-2144, 2012.Search in Google Scholar
A. Gaddam, S.C. Mukhopadhyay and G. Sen Gupta, Necessity of a Bed Sensor in a Smart Digital Home to Care for Elder-people, Proceedings of the 2008 IEEE Sensors conference, Lecce, Italy, October 26-28, 2008, page 1340-1343.10.1109/ICSENS.2008.4716693Search in Google Scholar
Novovicova J, Somol P, Haindl M, et al. Conditional Mutual Information Based Feature Selection for Classification Task, Proc of the 12th Iberoamericann Congress on Pattern Recognition, pp. 417-426, 2007.10.1007/978-3-540-76725-1_44Search in Google Scholar
N.K. Suryadevara, S.C. Mukhopadhyay, R. Wang, R.K. Rayudu, Forecasting the behavior of an elderly using wireless sensors data in a smart home, Engineering Applications of Artificial Intelligence, Volume 26, Issue 10, November 2013, Pages 2641-2652, ISSN 0952-1976, http://dx.doi.org/10.1016/j.engappai.2013.08.004.10.1016/j.engappai.2013.08.004Search in Google Scholar
Daode Zhang et al., Research on Chip Defect Extraction based on Image-Matching, International Journal on Smart Sensing and Intelligent Systems, vol. 7, no. 1, pp.321 – 336, 2014.10.21307/ijssis-2017-658Search in Google Scholar
N.K.Suryadevara, A. Gaddam, R.K.Rayudu and S.C. Mukhopadhyay, “Wireless Sensors Network based safe Home to care Elderly People: Behaviour Detection”, Sens. Actuators A: Phys. (2012), doi:10.1016/j.sna.2012.03.020, Volume 186, 2012, pp. 277 – 283.10.1016/j.sna.2012.03.020Search in Google Scholar
Yanmin LUO, Peizhong LIU and Minghong LIAO, An Artificial Immune Network Clustering Algorithm for Mangroves Remote Sensing Iamge,International Journal on Smart Sensing and Intelligent Systems, vol. 7, no. 1, pp. 116 – 134, 2014.10.21307/ijssis-2017-648Search in Google Scholar
