Research Article
Unsupervised Approach Data Analysis Based on Fuzzy Possibilistic Clustering: Application to Medical Image MRI
Let / the data sets, : the maximum number of iterations, : the number of the clusters, : the | matrix of membership degrees function, : the matrix of cluster center, : the fuzzy degree, Fuzzy_classification(): is the | function of fuzzy classification, F_obj(): the objective function, Possibilist_classification(): the possibilistic classification | function, : Degree of weight possibilistic, and : the threshold Representing the convergence error. | (1) Step . Initialize the parameters | (2) (i) | (3) (ii) Initialize the matrix by center clusters | (4) (iii) Initialize the matrix by membership degrees, random values in the interval | and it also satisfies the condition in (3). | (5) Step . Fuzzy process | (6) Repeat | (7) | (8) Compute: Fuzzy_classification ) // with (4) and (5) | (9) | (10) Until | (11) Step . Possibilist process | (12) // Initialize the matrix by | (13) // Initialize the matrix by | (14) Repeat | (15) | (16) Compute: Possibilist_classification ) // with (7) and (8) | (17) | (18) Until |
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