Research Article
Classification Based on the Optimal -Associated Network
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@INPROCEEDINGS{10.1007/978-3-642-02466-5_117, author={Alneu Lopes and Jo\"{a}o Bertini and Robson Motta and Liang Zhao}, title={Classification Based on the Optimal -Associated Network}, proceedings={Complex Sciences. First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009. Revised Papers, Part 1}, proceedings_a={COMPLEX PART 1}, year={2012}, month={5}, keywords={Complex Network Data Mining Data Classification Network formation}, doi={10.1007/978-3-642-02466-5_117} }- Alneu Lopes
João Bertini
Robson Motta
Liang Zhao
Year: 2012
Classification Based on the Optimal -Associated Network
COMPLEX PART 1
Springer
DOI: 10.1007/978-3-642-02466-5_117
Abstract
In this paper, we propose a new graph-based classifier which uses a special network, referred to as optimal , for modeling data. The -associated network is capable of representing (dis)similarity relationships among data samples and data classes. Here, we describe the main properties of the -associated network as well as the classification algorithm based on it. Experimental evaluation indicates that the model based on an optimal -associated network captures topological structure of the training data leading to good results on the classification task particularly for noisy data.
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