Initialization insensitive LVQ algorithm based on cost-function adaptation

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.