分类判别中，bayes判别的确具有明显的优势，与模糊，灰色，物元可拓相比，判别准确率一般都会高些，而BP神经网络由于调试麻烦，在调试过程中需要人工参与，而且存在明显的问题，局部极小点和精度与速度的矛盾，以及训练精度和仿真精度间的矛盾，等，尽管是非线性问题的一种重要方法，但是在我们项目中使用存在一定的局限，基于此，最近两天认真的研究了bayes判别，并写出bayes判别的matlab程序，与spss非逐步判别计算结果一致。-Classified Identifying, bayes discriminant does have a distinct advantage, with the fuzzy, gray, matter-element and extension compared to determine the exact rate will be higher in general, and the BP neural network trouble as a result of debugging, in the need to manually debug the process of participation, but also obvious problems, the local minimum point and the accuracy and speed of contradictions, as well as simulation training accuracy and precision of the conflict between, and so on, in spite of nonlinear problems is an important method, but the use of our project there are certain limitations, based on the Here, seriously the last couple of days to study the discriminant bayes and bayes discriminant of matlab to write procedures, and non-spss stepwise discriminant calculation results.