LVQ と多変量判別分析法の比較検討

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, In the case of the classification, where 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 basic properties of LVQ by using model data.