What is the impact of data granularity on association rule mining

Jun 16, 2010 ... Association rule mining is used to find the patterns in data.it finds the features which occur together and correlated. Maximum frequent pattern generation from a large database of transactions and items for association rule mining is an important research topic in data ... Jan 23, 2023 ... Association rule mining is an unsupervised machine learning technique because it does not require labeled training data. In association rule ... 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 ... Jan 11, 2023 ... This rule shows how frequently a itemset occurs in a transaction. A typical example is a Market Based Analysis. Jan 27, 2025 ... Association rules are derived through algorithms that evaluate the frequency and strength of these relationships. They use metrics like support, ... Abstract. Association rule mining (ARM) is a technique used to discover relationships among a large set of variables in a data set. It has been applied to ... Nov 12, 2020 ... Association rule mining data for census tract chemical exposure analysis ... Chemical concentration, exposure, and health risk data for U.S. ... Association rule learning ... Association rule learning is a rule-based machine learning method for discovering interesting relations between variables in large ... This paper presents a literature review to identify the newest and most cited ARM algorithms and techniques suitable for EA mining