An algorithm for discretization based on Particle swarm optimization (PSO) is presented, which can settle the problem of continuous attributes discretization in systema modeling perfectly.
提出了一种基于微粒群优化(PSO)算法的连续属性离散化方法，很好的解决了建模过程中连续属性的离散化问题。
Discretization of continuous type of attributes is a key issue in machine learning, it is a NP puzzle.
连续型属性的离散化问题是机器学习中的关键问题，是一个NP难题。
Because traditional rough set theory can only deal with the discrete attributes in database. So, the discretization of continuous attributes is one of the main problems in rough sets.
由于粗糙集只能对离散属性进行处理，因而连续属性的离散化也就成了粗糙集的主要问题之一。
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