What are the fault tolerance mechanisms in distributed association rule mining What are the specific algorithms designed for distributed association rule mining

Association rule mining (ARM) is a well-established data mining technique that has been commonly used for mining commercial transactional databases. Link ... Aug 25, 2018 ... The reason the Association Rule Learner Node is returning an empty table is that the minimum support is too high. Nov 29, 2023 ... In this paper, Enhanced Elephant Herding Optimization Algorithm for Association Rule Hiding (EEHOA4ARH) is proposed for association rule hiding. We developed a novel approach to infer interactions among transcription factors in user-selected genomic regions, by combining the computation of association ... In conclusion, association rule mining is a technique that discovers interesting relationships and patterns within large datasets. It involves identifying ... We developed methods for automatically identifying associations between medications and problems using association rule mining on a large clinical data ... Our research introduces a groundbreaking methodology called Fuzzy Association Rule Mining (FARM), combining fuzzy set theory with traditional Association Rule ... Jun 9, 2021 ... This paper introduces a heuristic approach based on divide-and-conquer which may exponentially reduce both the time complexity and memory usage. Nov 11, 2015 ... What is association analysis? How it works; How to measure rule strength; How to use association analysis with tabular data; When to use ... Rule generation is a common task in the mining of frequent patterns. An association rule is an implication expression of the form X→Y, where X and Y are ...