Saliency Analysis of Support Vector Machines for Feature Selection in Financial Time Series Forecasting
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[1] Wright-Patterson Afb,et al. Feature Selection Using a Multilayer Perceptron , 1990 .
[2] Kenneth W. Bauer,et al. Determining input features for multilayer perceptrons , 1995, Neurocomputing.
[3] Alexander J. Smola,et al. Support Vector Method for Function Approximation, Regression Estimation and Signal Processing , 1996, NIPS.
[4] Bernhard Schölkopf,et al. Learning with kernels , 2001 .
[5] Kenneth W. Bauer,et al. Feature saliency measures , 1997 .
[6] Russell Reed,et al. Pruning algorithms-a survey , 1993, IEEE Trans. Neural Networks.
[7] Jacek M. Zurada,et al. Perturbation method for deleting redundant inputs of perceptron networks , 1997, Neurocomputing.
[8] Bernhard Schölkopf,et al. A tutorial on support vector regression , 2004, Stat. Comput..
[9] William H. Murray,et al. Microsoft C/C++ 7: The Complete Reference , 1992 .
[10] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[11] F. Girosi,et al. Nonlinear prediction of chaotic time series using support vector machines , 1997, Neural Networks for Signal Processing VII. Proceedings of the 1997 IEEE Signal Processing Society Workshop.
[12] Victor L. Brailovsky,et al. On domain knowledge and feature selection using a support vector machine , 1999, Pattern Recognit. Lett..
[13] Patrick Gallinari,et al. Variable selection with neural networks , 1996, Neurocomputing.