Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Clustering is an important research area that has practical applications in many fields. Fuzzy clustering has shown advantages over crisp and probabilistic clustering, especially when there are significant overlaps beten clusters. Most analytic fuzzy clustering approaches are derived from Bezdek's fuzzy c-means algorithm. One major factor that influences the determination of appropriate clusters in these approaches is an exponent parameter, called the fuzzifier. To our knowledge, no theoretical reason leading to an optimal setting of this parameter is available.  presents the development of an heuristic scheme for determining the fuzzifier. This scheme creates close interactions beten the fuzzifier and the data set to be clustered. Experimental results in clustering IRIS data and in code book design required for image compression reveal a good performance of our proposal.
['Lotfi Ben Romdhane', 'Béchir el Ayeb', 'Shengrui Wang']
I am writing a research paper on a idea ON COMPUTING THE FUZZIFIER IN ↓FLVQ: A DATA DRIVEN APPROACH
[{"from": "human", "value": "I am writing a research paper on a idea ON COMPUTING THE FUZZIFIER IN \u2193FLVQ: A DATA DRIVEN APPROACH"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Clustering is an important research area that has practical applications in many fields. Fuzzy clustering has shown advantages over crisp and probabilistic clustering, especially when there are significant overlaps beten clusters. Most analytic fuzzy clustering approaches are derived from Bezdek's fuzzy c-means algorithm. One major factor that influences the determination of appropriate clusters in these approaches is an exponent parameter, called the fuzzifier. To our knowledge, no theoretical reason leading to an optimal setting of this parameter is available.  presents the development of an heuristic scheme for determining the fuzzifier. This scheme creates close interactions beten the fuzzifier and the data set to be clustered. Experimental results in clustering IRIS data and in code book design required for image compression reveal a good performance of our proposal."}]