欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
粗糙集理论中要求离散化保持原有决策系统的不可分辨关系，但以往的一些算法在离散过程中会使近似精度控制在可以接受的范围，即允许一定的错分。针对此不足，在保证决策属性绝对不改变的情况下，提出一种新的区间拆分方法，更合理有效地对连续属性进行离散化。实验通过C4．5和支持向量机分别对离散化后的数据进行识别与分类预测，实验结果证明了算法的有效性。
英文摘要：
The rough set required that discretization should be maintained indiscernibility of the original decision-making system, however, many algorithms before permitted approximate quality descended controlled certain scope. This paper proposed a novel method of splitting interval. The novel algorithm was more reasonable and effective to discretization of continual attribute, and assured not to change decision-making attributes. By using C4.5 and SVM, performed the experiments respectively with the results of discreted data. The experiment results show that the presented algorithm is effective.
同期刊论文项目
同项目期刊论文
期刊信息
位置：