Abstract: Knowledge-based fuzzy clustering algorithms can integrate prior knowledge, constraints or expert experience into the clustering process, thereby improving the interpretability and accuracy ...
HypeFCM is a fuzzy clustering algorithm for non-Euclidean spaces, combining hyperbolic geometry with adaptive weight-based filtering in the Poincaré Disc model. It efficiently captures hierarchical ...
HypeFCM is a fuzzy clustering algorithm for non-Euclidean spaces, combining hyperbolic geometry with adaptive weight-based filtering in the Poincaré Disc model. It efficiently captures hierarchical ...
Abstract: Most clustering validity indexes (CVIs) for fuzzy clustering are based upon the fuzzy c-means (FCMs) algorithm, and the effect of these CVIs is limited due to the “uniform effect” of FCM.
Marine communities around the world show trophic convergence in similar environments, complementing our understanding of the factors that determine the biogeography of marine species. The existence of ...
ABSTRACT: Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering ...
ABSTRACT: The early detection of type 2 diabetes is a major challenge for healthcare professionals, as a late diagnosis can lead to severe and difficult-to-manage complications. In this context, this ...
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