Cluster Analysis

Cluster analysis is an unsupervised machine learning technique aiming to group similar data points into clusters, revealing underlying structure and patterns within datasets. Current research emphasizes developing robust algorithms that handle high-dimensional data, address challenges like parameter sensitivity and bias, and improve interpretability through techniques such as graphical modeling and manifold learning. These advancements are crucial for diverse applications, including patient subgroup identification in healthcare, driving behavior analysis in transportation, and financial market analysis, ultimately leading to more insightful data interpretation and improved decision-making across various fields.