| 一种基于改进粒子群的连续属性离散化算法 |
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| 引用本文： | 汪凌. 一种基于改进粒子群的连续属性离散化算法[J]. 计算机工程与应用, 2013, 49(21): 29-32 |
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| 作者姓名： | 汪凌 |
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| 作者单位： | 1.北京交通大学 中国产业安全研究中心，北京 1000442.固体废物处理与环境安全教育部重点实验室，北京 100084 |
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| 基金项目： | 教育部人文社会科学研究青年基金项目(No.11YJC630195)；安徽省高校省级自然科学研究重点项目(No.KJ2012A076)；固体废物处理与环境安全教育部重点实验室开放基金项目(No.SWMES 2011-05)。 |
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| 摘 要： | 提出一种基于改进粒子群的连续属性离散化算法。该算法结合集群智能优化理论和粗糙集理论，将各属性离散化分割点初始化为粒子群体，通过粒子间的相互作用寻求最优离散化分割点。将提出的离散化算法应用于UCI数据集实验中，实验结果表明，该算法能使决策系统的信息损失降低到最小，并可获取更为简洁的决策规则。
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| 关 键 词： | 改进粒子群 智能优化 粗糙集 连续属性离散化 |
Algorithm of continuous attribute discretization based on improved particle swarm |
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| WANG Ling. Algorithm of continuous attribute discretization based on improved particle swarm[J]. Computer Engineering and Applications, 2013, 49(21): 29-32 |
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| Authors: | WANG Ling |
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| Affiliation: | 1.China Center for Industrial Security Research, Beijing Jiaotong University, Beijing 100044, China2.Key Lab for Solid Waste Management and Environment Safety, Ministry of Education of China, Beijing 100084, China |
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| Abstract: | An algorithm of continuous attribute discretization based on improved particle swarm is proposed. The algorithm combines intelligent optimization theory and rough sets theory. Each attribute discretization points are initialized to particle group, seeking the optimal discretization points through the interaction between particles. Discretization algorithm is applied to the UCI data sets in the experiment, and the experimental results show that, the algorithm can make the loss of information decision system reduce to the minimum, and get more concise decision rules. |
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| Keywords: | improved particle swarm intelligent optimization rough sets continuous attribute discretization |
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