Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...

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Department of Chemistry, University of Florida, Gainesville, Florida 32611, United States Quantum Theory Project, University of Florida, Gainesville, Florida 32611, United States ...

To continue reading this content, please enable JavaScript in your browser settings and refresh this page. Preview this article 1 min Portland-based Birch Biosciences ...

examples_distance.dat is one of the supplementary files in "Clustering by fast search and find of density peaks "sample.txt is an example dataset with 4000 instances ...

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: This paper presents a new algorithm for solving unit commitment (UC) problems using a binary-real coded genetic algorithm based on k-means clustering technique. UC is a NP-hard nonlinear ...