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Support vectors classification method based on projection vector boundary feature
Author(s): Yaqin Guo; Xin Song
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Paper Abstract

A support vectors classification Method Based on projection vector boundary feature is proposed. According to statistical theory and normal distribution characteristics in one-dimensional space, the proposed algorithm introduces a new definition of the margin, objective function is constructed in high-dimensional space, through solving the objective function, and projection line is obtained. After the training samples are projected to the line , we construct boundary vector sets in one-dimensional space, which are used to train support vector machine(SVM). Experiments on two artificial data sets and UCI standard data set show that the proposed method is effective.

Paper Details

Date Published: 9 August 2018
PDF: 5 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108060E (9 August 2018); doi: 10.1117/12.2503318
Show Author Affiliations
Yaqin Guo, Nantong Polytechnic College (China)
Xin Song, Nantong Polytechnic College (China)

Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)

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