Abstract: The traditional K-means algorithm often leads to unstable clustering quality due to the randomness of the initial clustering center selection and tends to fall into suboptimal solutions when ...
Abstract: The study applies a dataset comprising of more than 20,000 documents to a comprehensive comparative analysis of clustering algorithms: Mean Shift, Hierarchical and K-Means. The study's main ...
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