Intelligent method for sensor subset selection for machine olfaction
暂无分享,去创建一个
Vutipong Areekul | H. Troy Nagle | H. T. Nagle | Ekachai Phaisangittisagul | V. Areekul | E. Phaisangittisagul | H. Nagle
[1] Isabelle Guyon,et al. An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..
[2] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[3] H. L. Le Roy,et al. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability; Vol. IV , 1969 .
[4] Ron Kohavi,et al. Wrappers for Feature Subset Selection , 1997, Artif. Intell..
[5] O. Mangasarian,et al. Robust linear programming discrimination of two linearly inseparable sets , 1992 .
[6] Ron Kohavi,et al. Irrelevant Features and the Subset Selection Problem , 1994, ICML.
[7] Ricardo Gutierrez-Osuna,et al. The how and why of electronic noses , 1998 .
[8] J. Mesirov,et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.
[9] Ekachai Phaisangittisagul,et al. Outlier detection for machine olfaction based on odor-type signatures , 2009, 2009 6th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology.
[10] P. Langley. Selection of Relevant Features in Machine Learning , 1994 .
[11] Isabelle Guyon,et al. Automatic Capacity Tuning of Very Large VC-Dimension Classifiers , 1992, NIPS.
[12] Jason Weston,et al. Multi-Class Support Vector Machines , 1998 .
[13] Ekachai Phaisangittisagul,et al. Signal Processing using Wavelets for Enhancing Electronic Nose Performance , 2007 .
[14] M. Pardo,et al. Classification of electronic nose data with support vector machines , 2005 .
[15] Evor L. Hines,et al. Enhancing electronic nose performance by sensor selection using a new integer-based genetic algorithm approach , 2005 .
[16] Anil K. Jain,et al. Statistical Pattern Recognition: A Review , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[17] Zulfiqur Ali,et al. Data analysis for electronic nose systems , 2006 .
[18] Alan J. Miller,et al. Subset Selection in Regression , 1991 .
[19] Olvi L. Mangasarian,et al. Nonlinear Programming , 1969 .
[20] R. Fletcher. Practical Methods of Optimization , 1988 .
[21] N. Ancona,et al. Support vector machines for olfactory signals recognition , 2003 .
[22] H. Troy Nagle,et al. Sensor Selection for Machine Olfaction Based on Transient Feature Extraction , 2008, IEEE Transactions on Instrumentation and Measurement.
[23] Keinosuke Fukunaga,et al. A Branch and Bound Algorithm for Feature Subset Selection , 1977, IEEE Transactions on Computers.
[24] Chih-Jen Lin,et al. A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.
[25] E. Phaisangittisagul,et al. Transient feature extraction for machine olfaction based on Wavelet decomposition , 2008, 2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology.
[26] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[27] Marko Grobelnik,et al. Feature Selection Using Linear Support Vector Machines , 2002 .
[28] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[29] Christopher J. C. Burges,et al. A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.
[30] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[31] Lalita Udpa,et al. Artificial intelligence methods for selection of an optimized sensor array for identification of volatile organic compounds , 2001 .
[32] Ron Kohavi,et al. Wrappers for feature selection , 1997 .
[33] Alexander J. Smola,et al. Learning with Kernels: support vector machines, regularization, optimization, and beyond , 2001, Adaptive computation and machine learning series.
[34] Tomasz Markiewicz,et al. Classification of milk by means of an electronic nose and SVM neural network , 2004 .
[35] P. Travers,et al. A method for selecting an optimum sensor array , 2000 .