| 摘要 |
In this study, six main shoulder items for Chinese females were collected using 3D body scanner in 2015-2017. The Principal Component Analysis was used to determine the basic shoulder items for the shaping classification. Two principal components were extracted from 6 variables, which reflected most of the information of the original variables. The first principal component factor is the length factor; the second principal component is the angle factor. The most representative indexes are selected from the length factor and the angle factor by the correlation index maximum method, namely the shoulder width and the right shoulder oblique angle. The shoulder shaping clustering is based on the K- means clustering method. The clustering results shows that when the number of classes is 4, the proportion in the total number is 22.4%, 23.3%, 22.7% and 31.6% respectively, and the results are clear and the people in each class are relatively balanced. |