Methods: Principal component analysis and clustering analysis were used to group participants based on their levels of engagement, and the data analysis focused on characteristics (eg, age, sex, and ...

Abstract: The graph-information-based fuzzy clustering has shown promising results in various datasets. However, its performance is hindered when dealing with high-dimensional data due to challenges ...

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 ...