ParTree Data Partitioning through Treebased Clustering Method

Date: November 30, 2023

Presenter: Riccardo Guidotti

Location: Officine Garibaldi - il Cantiere delle Idee, Via Vincenzo Gioberti, 39, 56124 Pisa PI, Italy

Abstract: While existing clustering methods only provide the assignment of records to clusters without justifying the partitioning, we propose tree-based clustering methods that offer interpretable data partitioning through a shallow decision tree. These decision trees enable easy-to-understand explanations of cluster assignments through short and understandable split conditions. The proposed methods are evaluated through experiments on synthetic and real datasets and proved to be more effective than traditional clustering approaches and interpretable ones in terms of standard evaluation measures and runtime.