An Analysis of Convergence in Generalized LVQ
We have proposed a new formulation of Learning Vector Quantization (LVQ) called “Generalized LVQ” based on Minimum Classification Error (MCE). In this paper, we attempt to clarify the convergence property of reference vectors in our formulation. We discuss the equilibrium in a dynamical system for two-class classification, and prove that equilibrium states exist in our formulation, while they do not exist in LVQ2.1 or Juan & Katagiri’s formulation based on MCE.
KeywordsEquilibrium Point Discriminant Function Convergence Property Learning Rule Convergence Condition
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