A Reduction SVM Classification Algorithm Based on Adaptive AP Clustering Granulation

2014 ◽  
pp. 144-153
Author(s):  
Xiuxi Wei
Keyword(s):  
Classification Algorithm ◽  
Svm Classification ◽  
Ap Clustering

scholarly journals Improved SVM classification algorithm based on KFCM and LDA

2020 ◽  
Vol 1693 ◽  
pp. 012107
Author(s):  
Xiaoyan Zhang ◽  
Mengjuan Wang
Keyword(s):  
Classification Algorithm ◽  
Svm Classification

scholarly journals Obscure Image Classification and Restoration using Support Vector Machines

2019 ◽  
Vol 8 (4) ◽  
pp. 8231-8236
Keyword(s):  
Kernel Estimation ◽  
Classification Algorithm ◽  
Support Vector ◽  
Svm Classification ◽  
Vector Machines ◽  
Blurred Image ◽  
Simulation Results ◽  
Blurred Images ◽  
Identification And Characterization ◽  
Restoration Model

A restoration and classification computation for blurred image which depends on obscure identification and characterization is proposed in this paper. Initially, new obscure location calculation is proposed to recognize the Gaussian, Motion and Defocus based blurred locales in the image. The degradation-restoration model referred with pre-processing followed by binarization and features extraction/classification algorithm applied on obscure images. At this point, support vector machine (SVM) classification algorithm is proposed to cluster the blurred images. Once the obscure class of the locales is affirmed, the structure of the obscure kernels of the blurred images are affirmed. At that point, the obscure kernel estimation techniques are embraced to appraise the obscure kernels. At last, the blurred locales are re-established utilizing nonblind image deblurring calculation and supplant the blurred images with the restored images. The simulation results demonstrate that the proposed calculation performs well

Based on SVM Classification of Connection Pools Algorithm

2014 ◽  
Vol 945-949 ◽  
pp. 2435-2438
Author(s):  
Juan Zhao ◽  
Hui Yun Xiong
Keyword(s):  
Classification Algorithm ◽  
Experimental Results ◽  
Svm Classifier ◽  
Database Access ◽  
Service Platform ◽  
Buffer Pool ◽  
Svm Classification ◽  
Connection Pool

The connection pool technology has become a deal with large amount of data requested a solution that is widely used now. This paper used the SVM classification algorithm for classified all database requests quickly, so the corresponding database request could be assigned to different connection pool distribution. We applied the connection pool to measurement service platform and tested on the accuracy of the SVM classifier and buffer pool hit ratios of the connection pool module. The experimental results show that the connection pools can improve the efficiency of database access obviously.

scholarly journals An Efficient Multi-Label SVM Classification Algorithm by Combining Approximate Extreme Points Method and Divide-and-Conquer Strategy

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 170967-170975
Author(s):  
Zhongwei Sun ◽  
Xiuyan Liu ◽  
Keyong Hu ◽  
Zhuang Li ◽  
Jing Liu
Keyword(s):  
Extreme Points ◽  
Classification Algorithm ◽  
Divide And Conquer ◽  
Svm Classification
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