关键词: 多维尺度分析, 欧氏距离, 名义属性, 混合值差度量

Abstract: In general，Multidimensional Scaling（MDS） uses Euclidean distance to measure the dissimilarity（similarity） of objects.If objects have nominal attributes，such as sex or color，common practice is digitizing first and then applying Euclidean distance.Obviously，this approach is not reasonable to some extents.The Heterogeneous Value Difference Metric（HVDM），a distance metric computing distance for nominal attributes differently than Euclidean distance，is applied to MDS to improve its reasonableness on nominal attributes.Experimental results on UCI Abalone dataset show that the proposed method gives promising results on both reconstruction ability and accuracy.

Key words: Multidimensional Scaling（MDS）, Euclidean distance, nominal attribute, Heterogeneous Value Difference Metric（HVDM）