连续属性的离散化算法

摘要

结合聚类的思想与信息增益性质,给出一种基于距离与信息增益相结合的连续属性离散化方法.此方法不仅考虑了属性值之间的序关系,而且考虑了属性值之间的相对大小关系.此算法的一个最大优点是能自动调整离散化过程中的阈值,且能达到所要求的决策表相容度.%Combining the philosophy of clustering and information gain,a discretization algorithm based on distance and information gain is proposed. This method thinks over not only the ordinal relation of attribute values, but also the relative distance of attribute values. The prominent merit of this algorithm is that it can adjust the threshold automatic and satisfy the consistence degree requested.