Abstract: K-means clustering is a widely used unsupervised learning algorithm for partitioning data into distinct clusters. However, the performance of k-means heavily depends on the initial cluster ...

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 ...