| 光谱学与光谱分析 |
|
|
|
|
|
| Studies of Spectra Classification Based on Kernel Covering Algorithm |
| YANG Jin-fu1,XU Xin1,WU Fu-chao1,ZHAO Yong-heng2 |
1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080，China
2. National Astronomical Observatory, Chinese Academy of Sciences, Beijing 100012, China |
|
|
|
|
Abstract A kernel based covering algorithm, called the kernel covering algorithm (KCA), is proposed for the classification of celestial spectra. This algorithm is a combination of kernel trick with the covering algorithm, and is used to extract the support vectors in feature space. The experiments show that the classification result based on KCA is a little less than that based on SVM. However, KCA only involves the distance computation without the need to solve the quadratic programming problem. Also, KCA is insensitive to the width of gauss window. Although KCA has a comparable classification performance with the covering algorithm, it changes the distance between samples in feature space by the nonlinear mapping such that the distribution of samples is more adaptable to classify. Therefore, the number of KCA’s resulting support vectors is significantly smaller than that of the covering algorithm.
|
|
Received: 2005-12-06
Accepted: 2006-03-28
|
|
|
|
Corresponding Authors:
YANG Jin-fu
E-mail: yangjf@nlpr.ia.ac.cn
|
|
| Cite this article: |
|
YANG Jin-fu,XU Xin,WU Fu-chao, et al. Studies of Spectra Classification Based on Kernel Covering Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2007, 27(03): 602-605.
|
|
|
|
| URL: |
|
https://www.gpxygpfx.com/EN/Y2007/V27/I03/602 |
[1] LIU Rong, DUAN Fu-qing, LUO A-li(刘 蓉，段福庆，罗阿理). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2005，25(7)：1155.
[2] QIN Dong-mei, HU Zhan-yi, ZHAO Yong-heng(覃冬梅, 胡占义, 赵永恒). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2003, 23(1): 182.
[3] Cortes C，Vapnik V N. Machine Learning, 1995，20：273.
[4] Girosi F, Jones M, et al. Neural Computation, 1995，7(219): 269.
[5] Seeger Matthias. International Journal of Neural Systems, 2004，14(2): 1.
[6] Baudat G，Anouar F. Neural Computation, 2000，12(10)：2385.
[7] Scholkopf B, Smola A J, Müller K R. Neural Computation, 1998，10：1299.
[8] YANG Jin-fu, WU Fu-chao, LUO A-li，et al(杨金福，吴福朝，罗阿理，等). Pattern Recognition and Artificial Intelligence(模式识别与人工智能)，2006，19(3)：368.
[9] Zhang Ling，Zhang Bo. IEEE Transactions on Neural Networks, 1999，10(4)：925. |
| [1] |
BAO Hao1, 2，ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
| [2] |
CHENG Hui-zhu1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*, MA Qian1, 2, ZHAO Yan-chun1, 2. Genetic Algorithm Optimized BP Neural Network for Quantitative
Analysis of Soil Heavy Metals in XRF[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3742-3746. |
| [3] |
SHEN Si-cong, ZHANG Jing-xue, CHEN Ming-hui, LI Zhi-wei, SUN Sheng-nan, YAN Xue-bing*. Estimation of Above-Ground Biomass and Chlorophyll Content of
Different Alfalfa Varieties Based on UAV Multi-Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3847-3852. |
| [4] |
BAI Xue-bing1, 2, SONG Chang-ze1, ZHANG Qian-wei1, DAI Bin-xiu1, JIN Guo-jie1, 2, LIU Wen-zheng1, TAO Yong-sheng1, 2*. Rapid and Nndestructive Dagnosis Mthod for Posphate Dficiency in “Cabernet Sauvignon” Gape Laves by Vis/NIR Sectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3719-3725. |
| [5] |
HUANG Zhao-di1, CHEN Zai-liang2, WANG Chen3, TIAN Peng2, ZHANG Hai-liang2, XIE Chao-yong2*, LIU Xue-mei4*. Comparing Different Multivariate Calibration Methods Analyses for Measurement of Soil Properties Using Visible and Short Wave-Near
Infrared Spectroscopy Combined With Machine Learning Algorithms[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3535-3540. |
| [6] |
LI Wen-wen1, 2, LONG Chang-jiang1, 2, 4*, LI Shan-jun1, 2, 3, 4, CHEN Hong1, 2, 4. Detection of Mixed Pesticide Residues of Prochloraz and Imazalil in
Citrus Epidermis by Surface Enhanced Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3052-3058. |
| [7] |
LIU Fei1, TAN Jia-jin1*, XIE Gu-ai2, SU Jun3, YE Jian-ren1. Early Diagnosis of Pine Wilt Disease Based on Hyperspectral Data and Needle Resistivity[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3280-3285. |
| [8] |
MA Qian1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*, CHENG Hui-zhu1, 2, ZHAO Yan-chun1, 2. Research on Classification of Heavy Metal Pb in Honeysuckle Based on XRF and Transfer Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2729-2733. |
| [9] |
LÜ Shi-lei1, 2, 3, WANG Hong-wei1, LI Zhen1, 2, 3*, ZHOU Xu1, ZHAO Jing1. Hyperspectral Identification Model of Cantonese Tangerine Peel Based on BWO-SVM Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2894-2901. |
| [10] |
WANG Jun-jie1, YUAN Xi-ping2, 3, GAN Shu1, 2*, HU Lin1, ZHAO Hai-long1. Hyperspectral Identification Method of Typical Sedimentary Rocks in Lufeng Dinosaur Valley[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2855-2861. |
| [11] |
ZHANG Hai-liang1, XIE Chao-yong1, TIAN Peng1, ZHAN Bai-shao1, CHEN Zai-liang1, LUO Wei1*, LIU Xue-mei2*. Measurement of Soil Organic Matter and Total Nitrogen Based on Visible/Near Infrared Spectroscopy and Data-Driven Machine Learning Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2226-2231. |
| [12] |
LI Hao-dong1, 2, LI Ju-zi1*, CHEN Yan-lin1, HUANG Yu-jing1, Andy Hsitien Shen1*. Establishing Support Vector Machine SVM Recognition Model to Identify Jadeite Origin[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2252-2257. |
| [13] |
LI Bin, HAN Zhao-yang, WANG Qiu, SUN Zhao-xiang, LIU Yan-de*. Research on Bruise Level Detection of Loquat Based on Hyperspectral
Imaging Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1792-1799. |
| [14] |
WU Chao1, QIU Bo1*, PAN Zhi-ren1, LI Xiao-tong1, WANG Lin-qian1, CAO Guan-long1, KONG Xiao2. Application of Spectral and Metering Data Fusion Algorithm in Variable Star Classification[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1869-1874. |
| [15] |
LI Shuang-chuan, TU Liang-ping*, LI Xin, WANG Li-li. Besvm: A-Type Star Spectral Subtype Classification Algorithm Based on Transformer Feature Extraction[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(05): 1575-1581. |
|
|
|
|
