Research on Kernel Function Selection Simulation Based on SVM Classification

doi:10.3969/j.issn.1006-2475.2011.08.037

Computer and Modernization ›› 2011, Vol. 1 ›› Issue (8): 133-136.doi: 10.3969/j.issn.1006-2475.2011.08.037

• 计算机仿真 • Previous Articles Next Articles

Research on Kernel Function Selection Simulation Based on SVM Classification

SONG Hui¹, XUE Yun¹, ZHANG Liang-jun²

1. School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou 510006, China;2. Guangzhou Tiptech Software Co., Ltd., Guangzhou 510665, China

Received:2011-05-23 Revised:1900-01-01 Online:2011-08-10 Published:2011-08-10

Abstract

Abstract: The basic theory and realization of support vector machines are described. Then the kernel functions of SVM and its optimization problem are discussed. The different kernel function selections are carried out simulation experiments with glass identification database, iris plants database and car evaluation database of UCI. The simulation results show that the data of same type with different kernel function have different classification efficiency and there is great influence for classification efficiency with right selection of kernel function.

Key words: classification, SVM, kernel function

CLC Number:

TP183

SONG Hui;XUE Yun;ZHANG Liang-jun. Research on Kernel Function Selection Simulation Based on SVM Classification[J]. Computer and Modernization, 2011, 1(8): 133-136.

[1]	MENG Na, FANG Wei-wei, LU Hong-ying. A DNN Compression Method for Environmental Sound Classification on Microcontroller Unit [J]. Computer and Modernization, 2024, 0(01): 80-86.
[2]	QIU Kai-xing, FENG Guang. A Multi-label Image Classification Model Based on Dual Feature Attention [J]. Computer and Modernization, 2023, 0(12): 41-47.
[3]	TANG Shi-qi, ZHOU Rui-ping, XIE Shi-bin, LIU Meng-chi, XIAO Wen, . Cross-language Multi-label Sentiment Classification Based on Stacked Denoising AutoEncoder [J]. Computer and Modernization, 2023, 0(11): 6-12.
[4]	WU Tian, LIU Hai-hua, TONG Shun-yan. Image Classification Based on Deep Feedback CNN [J]. Computer and Modernization, 2023, 0(09): 82-86.
[5]	MA Guo-xiang, YANG Ling-fei, YAN Chuan-bo, ZHANG Zhi-hao, SUN Bing, WANG Xiao-rong. Ultrasonic Image Diagnosis of Hepatic Echinococcosis Based on Deep DenseNet Network [J]. Computer and Modernization, 2023, 0(09): 100-104.
[6]	OUYANG Fei, WU Xu, XIANG Dong-sheng. Garbage Classification and Detection Method Based on Improved YOLOX [J]. Computer and Modernization, 2023, 0(08): 68-73.
[7]	LI Lan-lan, GAO Jian-long, ZHU Xiao, MU Pei-zheng. Insertion/Deletion Genomic Variations Detection Method Based on Regional Read#br# Segments Classification#br# [J]. Computer and Modernization, 2023, 0(07): 13-19.
[8]	YANG Sun-zhe, SUN Ai-zhen. Rice Nitrogen Nutrition Diagnosis Based on HSV Color and LBP Texture Features [J]. Computer and Modernization, 2023, 0(07): 86-92.
[9]	QIN Zhu-yuan, WU Hao-zhong, TAN Dai-qing, HAN Ai-qing, ZANG Hao, WANG Xuan, TANG Yan. Fine-grained Identification of Maidong Based on Multi-scale ResNet Combining Attention Mechanism [J]. Computer and Modernization, 2023, 0(07): 105-111.
[10]	ZHU Jian-bo, GE Ming-feng, DONG Wen-fei. Alzheimer’s Disease Image Classification Based on Improved EfficientNet [J]. Computer and Modernization, 2023, 0(06): 56-61.
[11]	HUA Xin-yu, QI Yun-song. A Hybrid Brain Tumor Classfication Study Based on CBAM and EfficientNet with Improved Channel Attention [J]. Computer and Modernization, 2023, 0(05): 1-7.
[12]	WANG Jie, PAN Feng, ZHANG Yan-sha, TAN Mian, YAN Xiao-bo, WANG Lin, . Surface Defect Classification of Aluminum Profiles with Weighted Non-local Modules [J]. Computer and Modernization, 2023, 0(05): 86-92.
[13]	XU Ya-xin, HE Ze-en, XU Xu-kan. Automatic Classification Method of CNC Machine Tool Fault Text Based on CNN-BiLSTM [J]. Computer and Modernization, 2023, 0(04): 7-14.
[14]	WEI Xin, HE Xiao-hai, TENG Qi-zhi, QING Lin-bo, CHEN Hong-gang. Event Extraction Method Based on BERT-BiLSTM-Attention Hybrid Model [J]. Computer and Modernization, 2023, 0(04): 26-31.
[15]	ZHU Yuan-ye, NI Jian-jun, TANG Guang-yi. An RGB-D Indoor Scene Classification Method Based on Improved Convolutional Neural Network [J]. Computer and Modernization, 2023, 0(04): 73-77.

Research on Kernel Function Selection Simulation Based on SVM Classification

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments