Fuzzy clustering with weighting of data variables
We introduce an objective function-based fuzzy clustering technique that assigns one influence parameter to each single data variable for each cluster. Our method is not only suited to detect structures or groups of data that are not uniformly distributed over the structure's single domains, but gives also information about the influence of individual variables on the detected groups. In addition, our approach can be seen as a generalization of the well-known fuzzy c-means clustering algorithm.
fuzzy clustering variable selection generalized fuzzy c-means