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Clustering algorithms (Semi-Supervised and Unsupervised)

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Clustering-Algorithms

Clustering algorithms (Semi-Supervised and Unsupervised)

FCM Function:

In -> A DataSet as data.frame or matrix, The Centroids as data.frame or matrix, The Distance as string, containing "euclidian" or "mahalanobis" (optional, "mahalanobis" as defaut), A threshold limiar to stop the clustering, (optional, 0.01 as defaut) and a iteration max number (optional, using threshold as defaut)

Out -> The centroid matrix, The number of elements in each centroid (Considering the greater membership value of Ui), A matrix containing the membership U, The iteration number of clustering

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Clustering algorithms (Semi-Supervised and Unsupervised)

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