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A Simple Heuristic for Classification with Ant-Miner Using a Population

机译:一种使用种群进行蚂蚁矿工分类的简单启发式方法

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Ant-Miner is an Ant Colony Optimization algorithm for classification task. This paper proposes an improved version of Ant-Miner, named mAnt-Miner+, which is based on mAnt-Miner (Ant-Miner that uses a population of many ants). mAnt-Miner+ uses a simple and invariable heuristic strategy, that avoids it easily trapping in the local optimal solution and improves the efficiency of the algorithm. mAnt-Miner+ has been compared against Ant-Miner and mAnt-Miner in six public domain data sets. The results show that: 1) in term of predictive accuracy, mAnt-Miner+ is competitive with Ant-Miner and better than mAnt-Miner; 2) mAnt-Miner+ is faster than Ant-Miner and mAnt-Miner; 3) the difference of the rule simplicity between three algorithms is small.
机译:Ant-Miner是用于分类任务的蚁群优化算法。本文提出了一个改进版本的Ant-Miner,名为mAnt-Miner +,它基于mAnt-Miner(使用许多蚂蚁的种群的Ant-Miner)。 mAnt-Miner +使用一种简单且不变的启发式策略,可以避免它容易陷入局部最优解中并提高算法的效率。已在六个公共领域数据集中将mAnt-Miner +与Ant-Miner和mAnt-Miner进行了比较。结果表明:1)在预测准确性上,mAnt-Miner +与Ant-Miner具有竞争优势,且优于mAnt-Miner。 2)mAnt-Miner +比Ant-Miner和mAnt-Miner快; 3)三种算法之间的规则简单性差异很小。

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