Abstract
The graphical representation or graphical analysis for multi-dimensional data in multivariate analysis is a very useful method. But it rarely is used to the pattern recognition field. The paper we use the stat plot to represent one observation or sample with multi variances and extract the new graphical features of star plot: sub-area features and sub-barycentre features. The new features are used for the K nearest neighbor classifier (KNN) with leave one out cross validation. Experiments with several standard benchmark data sets show the effectiveness of the new graphical features.
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© 2007 Springer-Verlag Berlin Heidelberg
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Wang, J., Hong, W., Li, X. (2007). The New Graphical Features of Star Plot for K Nearest Neighbor Classifier. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2007. Lecture Notes in Computer Science(), vol 4682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74205-0_96
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DOI: https://doi.org/10.1007/978-3-540-74205-0_96
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74201-2
Online ISBN: 978-3-540-74205-0
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