基于二进制可辨矩阵的肝功能检测数据约简方法

基于二进制可辨矩阵的数据约简方法具有直观性和可操作性的特点，因而在实际应用中受到开发人员的青睐。但已有的此类方法通常是在扫描数据集的过程中不加“削减”地直接产生大规模的二进制可辨矩阵，这导致较大的时间和空间开销。为此，利用对行的吸收律和逻辑和实现了对二进制可辨矩阵的规模进行有效缩减，构造一种新的基于二进制可辨矩阵的数据约简算法。它具有更好的可操作性，易于编程实现，其时间和空间复杂度都得到了较大的改善。在与某医院合作开发的项目中，该算法的应用已经进入测试阶段，可以较好完成了对肝功能检测数据（定性的数据）的约简，结果令人满意。

Reduction approach to detected data of liver function based on binary discernibility matrix

Binary discernibility matrix-based reduction approaches are characterized by vivacity and operability,which make them widely applied to projects.However,in existing approaches,binary discernibility matrixes with large scale are usually produced when scanning data set,and are used for reduction.This leads to excessive consumption time.In this paper,the scale of binary discernibility matrix are greatly reduced by using absorption law on row and logic addition,and a reduction algorithm based on binary discernibility matrix is proposed.This algorithm is characterized by good operability and feasibility,and its time and space complexity are relatively reduced.In the developing project,the proposed algorithm has been used,which is used to acquire knowledge in detected data of liver function,and the result is satisfactory.