Outlier Detection with Cluster Catch Digraphs: A Novel Approach for High-Dimensional and Arbitrary-Shaped Clusters

The paper introduces a novel family of outlier detection algorithms based on Cluster Catch Digraphs (CCDs) that are designed to address the challenges of high dimensionality and varying cluster shapes, which deteriorate the performance of most traditional outlier detection methods.