Abstract
Linear Laplacian Discrimination (LLD) as a non-linear feature extraction method has obtained very extensive applications. However, LDD suffers from the small sample size problem (SSS) and/or the type of the sample space when it is used. In order to circumvent such shortcomings, in this paper a Laplacian Maximum Scatter Difference Discriminant Criterion (LMSDC) is proposed by using new contextual-distance metric and integrating maximum scatter difference discriminant criterion(MSDC) into LDD. The proposed criterion can obviously decrease the dependence on the sample space and solve small sample size problem. The experimental results indicate the above advantages of the proposed method LMSDC.
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Gao, J., Xiang, L. (2011). Laplacian Maximum Scatter Difference Discriminant Criterion. In: Zeng, D. (eds) Applied Informatics and Communication. ICAIC 2011. Communications in Computer and Information Science, vol 224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23214-5_88
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DOI: https://doi.org/10.1007/978-3-642-23214-5_88
Publisher Name: Springer, Berlin, Heidelberg
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