SEST is a KPI-conditioned hierarchical clustering architecture that explains metric movements with cluster-based, node-level descriptions instead of predicate rules, but it is not yet validated.
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Self-Explaining Segment Trees: A KPI-Conditioned Segmentation Framework for Business Analytics with Node-Level Explanation via Recursive Subspace Partitioning
SEST is a KPI-conditioned hierarchical clustering architecture that explains metric movements with cluster-based, node-level descriptions instead of predicate rules, but it is not yet validated.