关键词: 女性体型, 体型分类, 判别模型, 随机森林, 特征变量

Abstract: Abstract: Clothing fit is a problem of demanding prompt solution in the present apparel industries. In order to determine the true shape of female body accurately, the large number of measurement data of 730 female subjects aging 18-50 was analyzed and six characteristic factors were extracted by factors analysis. Female figure was classified from the three levels, including the whole body type，local morphological characteristics and figure silhouette. According to it, prediction model of female body shape was established by using the algorithm of random forests, and the programmed tool was R language. The results showed that three of the random forest classifiers had high accuracy of prediction, which was up to 85% both for train samples and for test samples. It suggested that the prediction model was reliable for female figure identification. Further, the vital characteristic variables featuring female body shape were filtered by using random forest variable importance measures.

Key words: female body shape, body shape classification, prediction model, random forest, characteristic variables