该分解算法的计算时间复杂度远小于经典粗糙集约简算法的计算时间复杂度，在提高计算速度的同时不会损失信息量。
Time complexity of this decomposition algorithm is far less than the classical reduction method in RST, speed of calculation is raised and information are not loss.
把粗糙集理论与基于概率统计ID3算法结合建立粗糙集约简模型，可处理不精确和模糊数据集信息。
The rough sets reduction model is established by integrating rough sets theory with ID3 algorithm based on statistics, uncertainty fuzzy data set information can be processed with the model.
应用推荐