A PSO-Based Classification Rule Mining Algorithm
作者： Ziqiang Wang , Xia Sun , Dexian Zhang
DOI: 10.1007/978-3-540-74205-0_42
关键词: Classification rule 、 Computer science 、 Set (abstract data type) 、 One-class classification 、 Training set 、 Particle swarm optimization 、 Machine learning 、 Classification rule mining 、 Field (computer science) 、 Artificial intelligence 、 Algorithm 、 FSA-Red Algorithm 、 Data mining
摘要: Classification rule mining is one of the important problems in emerging field data which aimed at finding a small set rules from training with predetermined targets. To efficiently mine classification databases, novel algorithm based on particle swarm optimization (PSO) was proposed. The experimental results show that proposed achieved higher predictive accuracy and much smaller list than other algorithm.
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