Classification Based on the Optimal -Associated Network

Alneu Lopes; João Bertini; Robson Motta; Liang Zhao

Complex Sciences. First International Conference, Complex 2009, Shanghai, China, February 23-25, 2009. Revised Papers, Part 1

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

Alneu Lopes¹^,*, João Bertini¹^,*, Robson Motta¹^,*, Liang Zhao¹^,*

1: University of São Paulo

*Contact email: alneu@icmc.usp.br, bertini@icmc.usp.br, rmotta@icmc.usp.br, zhao@icmc.usp.br

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.

Keywords: Complex Network Data Mining Data Classification Network formation

Published: 2012-05-11

: http://dx.doi.org/10.1007/978-3-642-02466-5_117