AIFeb 16, 2015
A Generalization of Gustafson-Kessel Algorithm Using a New Constraint Parameter
arXiv:1502.04495v12 citations
AI Analysis
This work addresses clustering challenges in data analysis, but it appears incremental as it builds upon an existing method.
The paper tackles the problem of fuzzy clustering by introducing a new algorithm that generalizes the Gustafson-Kessel algorithm using a dissimilarity function with three parameters, resulting in a more flexible clustering approach.
In this paper one presents a new fuzzy clustering algorithm based on a dissimilarity function determined by three parameters. This algorithm can be considered a generalization of the Gustafson-Kessel algorithm for fuzzy clustering.