Abstract
Affective design, which aims to design favorable products that meet the customers affective needs and address customers affective satisfaction, has gain increasing attention in modern industries. This paper proposed an affective design approach combing random forest regression and association rule mining, where random forest is adopted to reduce the dimension of design elements and association rules is used to map the affective need to design element. The efficiency of the method is demonstrated by an application of elevator design.
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