ワインデータの解析に使用する多変量解析と LVQ 解析について

抄録

Kohonen's LVQ (Learning vector quantization) is a method for classification. LVQ does not require a normal distribution of data. On the other hand, the multivariate discriminant analysis method is based on a normal distribution of data. If data is not normally distributed, LVQ could have a better accuracy. Parameter setting such as the number of codebook vectors is arbitrary for LVQ. It is an advantage but could be a disadvantage oppositely. In this study, we report the comparison of Multivariate analysis and LVQ analysis.