Adaptive micro partition and hierarchical merging for accurate mixed data clustering
Abstract Heterogeneous attribute data (also called mixed data), characterized by attributes with numerical and categorical values, occur frequently across various scenarios.Since the annotation cost is high, Enamel Flower Tea Cup clustering has emerged as a favorable technique for analyzing unlabeled mixed data.To address the complex real-world clu