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A Systematic Assessment of Numerical Association Rule Mining Methods., , , , , and . SN Comput. Sci., 2 (5): 348 (2021)Why Not to Trust Big Data: Discussing Statistical Paradoxes., , , , , , and . DASFAA (Workshops), volume 13248 of Lecture Notes in Computer Science, page 50-63. Springer, (2022)Impact-Driven Discretization of Numerical Factors: Case of Two- and Three-Partitioning., , , and . BDA, volume 13147 of Lecture Notes in Computer Science, page 244-260. Springer, (2021)Big Data Analytics in Association Rule Mining: A Systematic Literature Review., , , , , , and . BDET, page 40-49. ACM, (2021)On Observing Patterns of Correlations During Drill-Down., , , , and . iiWAS, volume 14416 of Lecture Notes in Computer Science, page 134-143. Springer, (2023)An Analysis of Human Perception of Partitions of Numerical Factor Domains., , , , and . iiWAS, volume 13635 of Lecture Notes in Computer Science, page 137-144. Springer, (2022)Exploring Factors in a Crossroad Dataset Using Cluster-Based Association Rule Mining., , , , , and . ANT/EDI40, volume 201 of Procedia Computer Science, page 231-238. Elsevier, (2022)Detecting Simpson's Paradox: A Machine Learning Perspective., , , , , and . DEXA (1), volume 13426 of Lecture Notes in Computer Science, page 323-335. Springer, (2022)Grand Reports: A Tool for Generalizing Association Rule Mining to Numeric Target Values., , , , and . DaWaK, volume 12393 of Lecture Notes in Computer Science, page 28-37. Springer, (2020)Expected vs. Unexpected: Selecting Right Measures of Interestingness., , , , and . DaWaK, volume 12393 of Lecture Notes in Computer Science, page 38-47. Springer, (2020)