FCM Clustering Algorithm Utilizing the Quadratic Mean Shadow Set
In order to reduce the classification error caused by using constant values to define the five value membership function of shadow sets in five regions,a FCM clustering algorithm based on quadratic mean shadow sets(FCM-5QSS)was constructed using the average membership degree.Firstly,the membership matrix between objects and clusters is obtained through the FCM algorithm;Then,the average membership degree is used to define the five value membership function of the shadow set,and two pairs of thresholds are obtained through the properties of fuzziness and the principle of uncertainty balance.The objects corresponding to the membership degree are then divided into five regions;Finally,the clustering results are obtained by dividing the object clusters with membership degrees in the core and sub core regions.The experimental results on 8 UCI public datasets demonstrate the effectiveness of the proposed method.
three branch decision-makingfive region shadow setaverage membership degreethree branch clustering
万方数据
维普
