Initialization insensitive LVQ algorithm based on cost-function adaptation
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摘要
A learning vector quantization (LVQ) algorithm called harmonic to minimum LVQ algorithm (H2M-LVQ)1 is presented to tackle the initialization sensitiveness problem associated with the original generalized LVQ (GLVQ) algorithm. Experimental results show superior performance of the H2M-LVQ algorithm over the GLVQ and one of its variants on several datasets.
论文关键词：Generalized learning vector quantization,Harmonic average distance,Initialization sensitiveness
论文评审过程：Received 25 October 2004, Accepted 8 November 2004, Available online 28 January 2005.
论文官网地址：https://doi.org/10.1016/j.patcog.2004.11.011
