MATEC Web of Conferences
Volume 28, 20152015 the 4th International Conference on Advances in Mechanics Engineering (ICAME 2015)
|Number of page(s)||5|
|Section||Computer theory and Application Technology|
|Published online||28 October 2015|
Preserving Global and Local Structures for Supervised Dimensionality Reduction
School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang, 212003, China
2 Department of Information Technology, Clayton State University, Morrow, GA, 30260, China
a Corresponding author: email@example.com
In this paper, we develop a new approach for dimensionality reduction of labeled data. This approach integrates both global and local structures of data into a new objective, we show that the objective can be optimized by solving an eigenvalue problem. Testing results on benchmark data sets show that this new approach can effectively capture both the crucial global and local structures of data and thus lead to more accurate results for dimensionality reduction than existing approaches.
© Owned by the authors, published by EDP Sciences, 2015
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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