Participatory Learning in Fuzzy Clustering

This work suggests an unsupervised fuzzy clustering algorithm based on the concept of participatory learning introduced by Yager in the nineties. The performance of the algorithm is verified with synthetic data sets and with the well-known Iris data. In both circumstances the participatory learning algorithm determines the expected number of clusters and the corresponding cluster centers successfully. Comparisons with Gustafson-Kessel (GK) and modified fuzzy k-means (MFKM) are included to show the effectiveness of the participatory approach in data clustering