On feature selection with principal component analysis for one-class SVM
Tài liệu tham khảo
Bingham, 2001, Random projection in dimensionality reduction: applications to image and text data, 245
Blum, 1997, Selection of relevant features and examples in machine learning, Artificial intelligence, 97, 245, 10.1016/S0004-3702(97)00063-5
Chang, C.C., Lin, C.J., 2001. Libsvm: A Library for Support Vector MachinesSoftware. Available at http://www.csie.ntu.edu.tw/cjlin/libsvm.
Chen, Y., Zhou, X.S., Huang, T.S., 2001. One-class svm for learning in image retrieval. In: Proceedings of International Conference on Image Processing, pp. 34–37.
Choi, 2009, Least squares one-class support vector machine, Pattern Recognition Letters, 30, 1236, 10.1016/j.patrec.2009.05.007
Fei-Fei, 2007, Learning generative visual models from few training examples: an incremental bayesian approach tested on 101 object categories, Computer Vision and Image Understanding, 106, 59, 10.1016/j.cviu.2005.09.012
Feng, 2011, A recognition and novelty detection approach based on curvelet transform, nonlinear pca and svm with application to indicator diagram diagnosis, Expert Systems with Applications, 38, 12721, 10.1016/j.eswa.2011.04.060
Frome, A., Singer, Y., Sha, F., Malik, J., 2007. Learning globally-consistent local distance functions for shape-based image retrieval and classification. In: International Conference on Computer Vision, pp. 1–8.
Guyon, 2002, Gene selection for cancer classification using support vector machines, Machine Learning, 46, 389, 10.1023/A:1012487302797
Hoffmann, 2007, Kernel pca for novelty detection, Pattern Recognition, 40, 863, 10.1016/j.patcog.2006.07.009
Iplikci, 2006, Support vector machines-based generalized predictive control, International Journal of Robust and Nonlinear Control, 16, 843, 10.1002/rnc.1094
Kohavi, 1997, Wrappers for feature subset selection, Artificial intelligence, 97, 273, 10.1016/S0004-3702(97)00043-X
Lazebnik, S., Schmid, C., Ponce, J., 2006. Beyond bags of features: spatial pyramid matching for recognizing natural scene categories. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 2169–2178.
Lee, 2000, Breast cancer survival and chemotherapy: a support vector machine analysis, DIMACS Series in Discrete Mathematics and Theoretical Computer Science, 55, 1, 10.1090/dimacs/055/01
Liu, C., Wang, G., Ning, W., Lin, X., Li, L., Liu, Z., 2010. Anomaly detection in surveillance video using motion direction statistics. In: 2010 17th IEEE International Conference on Image Processing (ICIP), pp. 717–720.
Liu, 2003, Bayesian clustering with variable and transformation selections, Bayesian Statistics, 7, 249
Lowe, D., 2000. Towards a computational model for object recognition in it cortex. In: International Conference on Computer Vision, pp. 141–155.
Massy, 1965, Principal components regression in exploratory statistical research, Journal of the American Statistical Association, 60, 234, 10.1080/01621459.1965.10480787
Mazanec, 2008, Support vector machines, pca and lda in face recognition, Journal of Electrical Engineering, 59, 203
Schölkopf, 2001, Estimating the support of a high-dimensional distribution, Neural Computation, 13, 1443, 10.1162/089976601750264965
Vapnik, 2002, An overview of statistical learning theory, IEEE Transactions on Neural Networks, 10, 988, 10.1109/72.788640
Wan, 2010, An automatic pipeline monitoring system based on pca and svm, International Journal of Engineering and Applied Sciences, 6, 126