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Feature Selection Using SVM Probabilistic Outputs.

K. Shen, C. Ong, X. Li, H. Zheng, and E. Wilder-Smith. ICONIP (1), volume 4232 of Lecture Notes in Computer Science, page 782-791. Springer, (2006)

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M.Sc. Yunxuan Li University of Stuttgart

Yu Li University of Stuttgart

Univ. -Prof. Dr. Heng Xiao University of Stuttgart

Yang Xiao University of Stuttgart

Xiao Fei University of Stuttgart

Other publications of authors with the same name

Feature selection via sensitivity analysis of SVM probabilistic outputs.K. Shen, C. Ong, X. Li, and E. Wilder-Smith. Machine Learning, 70 (1): 1-20 (2008)Automatic EEG Artifact Removal: A Weighted Support Vector Machine Approach With Error Correction.S. Shao, K. Shen, C. Ong, E. Wilder-Smith, and X. Li. IEEE Trans. Biomed. Engineering, 56 (2): 336-344 (2009)Feature Selection Using SVM Probabilistic Outputs.K. Shen, C. Ong, X. Li, H. Zheng, and E. Wilder-Smith. ICONIP (1), volume 4232 of Lecture Notes in Computer Science, page 782-791. Springer, (2006)Automatic identification and removal of artifacts in EEG using a probabilistic multi-class SVM approach with error correction.S. Shao, K. Shen, C. Ong, X. Li, and E. Wilder-Smith. SMC, page 1134-1139. IEEE, (2008)X-ray pulsar-based navigation using pulse phase and Doppler frequency measurements.M. fan Xue, X. ping Li, L. Fu, H. yan Fang, H. feng Sun, and L. rong Shen. SCIENCE CHINA Information Sciences, 58 (12): 1-14 (2015)A content-based dynamic load-balancing algorithm for heterogeneous web server cluster.L. Zhang, X. Li, and S. Yuan. Comput. Sci. Inf. Syst., 7 (1): 153-162 (2010)Feature selection via sensitivity analysis of MLP probabilistic outputs.J. Yang, K. Shen, C. Ong, and X. Li. SMC, page 774-779. IEEE, (2008)Novel multi-class feature selection methods using sensitivity analysis of posterior probabilities.K. Shen, C. Ong, X. Li, and E. Wilder-Smith. SMC, page 1116-1121. IEEE, (2008)A Feature Selection Method for Multilevel Mental Fatigue EEG Classification.K. Shen, C. Ong, X. Li, H. Zheng, and E. Wilder-Smith. IEEE Trans. Biomed. Engineering, 54 (7): 1231-1237 (2007)Novel Tools for Driving Fatigue Prediction: (1) Dry Eeg Sensor and (2) Eye Tracker.F. Tey, S. Lin, Y. Tan, X. Li, A. Phillipou, and L. Abel. HCI (24), volume 8027 of Lecture Notes in Computer Science, page 618-627. Springer, (2013)