Feature Selection Algorithm Application in Near-Infrared Spectroscopy Classification Based on Binary Search Combined with Random Forest Pruning

Liu Ming; Li Zhongren; Zhang Haitao; Yu Chunxia; Tang Xinghong; Ding Xiangqian

doi:10.3788/lop54.103001

[1] Sun Tong, Wu Yiqing, Li Xiaozhen, et al. Discrimination of camellia oil adulteration by NIR spectra and subwindow permutation analysis［J］. Acta Optica Sinica, 2015, 35(6): 0630005.

[2] Liu Wei, Chang Qingrui, Guo Man, et al. Detection of leaf nitrogen content of summer corn using visible/near infrared spectra［J］. Journal of Infrared and Millimeter Waves, 2011, 30(1): 48-54.

[3] Chen Xiaofeng, Long Changjiang, Niu Zhiyou, et al. Classification research of Chinese medicine based on latent semantic analysis and NIR［J］. Acta Optica Sinica, 2014, 34(9): 0930001.

[4] Li Huimei, Liu Gang, Ou Quanhong, et al. Analysis of eight bean species by two-dimensional correlation infrared spectroscopy［J］. Laser & Optoelectronics Progress, 2016, 53(3): 033003.

[5] Chu Xiaoli, Lu Wanzhen. Research and application progress of near infrared spectroscopy analytical technology in China in the past five years［J］. Spectroscopy Spectral Analysis, 2014, 34(10): 2595-2605.

[6] Guo Zhiming, Huang Wenqian, Peng Yankun, et al. Adaptive ant colony optimization approach to characteristic wavelength selection of NIR spectroscopy［J］. Chinese Journal of Analytical Chemistry, 2014, 42(4): 513-518.

[7] Fang Kuangnan, Wu Jianbin, Zhu Jianping, et al. A review of technologies on random forests［J］. Statistics & Information Forum, 2011, 26(3): 32-38.

[8] Zhang Aiwu, Xiao Tao, Duan Yihao, et al. A method of adaptive feature selection for airborne LiDAR point cloud classification［J］. Laser & Optoelectronics Progress, 2016, 53(8): 082802.

[9] Yang Junwen, Zhang Jinshui, Zhu Xiufang, et al. Random forest applied for dimension reduction and classification in hyperspectral data［J］. Journal of Beijing Normal University (Natural Science Edition), 2015, 51(s1): 82-88.

[10] Yao Dengju, Yang Jing, Zhan Xiaojuan. Feature selection algorithm based on random forest［J］. Journal of Jilin University (Engineering and Technology Edition), 2014, 44(1): 137-141.

[11] Xu Yonggang, Zhang Jianye, Gong Xiaogang, et al. A method of real-time traffic classification in secure access of the power enterprise based on improved random forest algorithm［J］. Power System Protection and Control, 2016, 44(24): 82-89.

[12] Breiman L. Random forests［J］. Machine Learning, 2001, 45(1): 5-32.

[13] Zhang Shihui, He Huan, Kong Lingfu, et al. Fusing multi-feature for video occlusion region detection based on graph cut［J］. Acta Optica Sinica, 2015, 35(4): 0415001.

[14] Tang Wei, Liu Fengnian, Chen Chongbang, et al. Application of improved Gini index in the text classification［J］. Journal of Changsha University, 2013, 27(5): 55-63.

[15] Fan W L, Hu P, Liu Z G. Multi-attribute node importance evaluation method based on Gini-coefficient in complex power grids［J］. IET Generation, Transmission & Distribution, 2016, 10(9): 2027-2034.

[16] Yang F, Lu W H, Luo L K, et al. Margin optimization based pruning for random forest［J］. Neurocomputing, 2012, 94: 54-63.