Density-Based Heuristic for Rule Discovery with Ant-Miner
作者： Hussien A. Abbass , Bo Liu , Bob Mckay
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摘要: Ant-Miner is an Ant colony Optimization (ACO) algorithm for rule discovery in database. The method was originally introduced by (Parepinelli, Lopes, & Freitas, 2002) and has shown comparable results to existing methods the literature. heuristic value used based on concept of entropy. While this motivated information theoretic measures, it seems that with idea using pheromone values ACO, ants can recover easily without computationally expensive concept. In paper, we present a simple sample density estimation easy compute does not resuire calculations logs as Ant-Miner. We show our proposed method, initial analysis, performs exactly same
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