1.　　采用BP神经网络设计男女生分类器。采用的特征包括身高、体重、是否喜欢数学、是否喜欢文学、是否喜欢运动共五个特征，BP神经网络包含一个隐层，隐层结点数为5。要求：自行编写代码完成后向传播算法，采用交叉验证的方式实现对于性能指标的评判（包含SE,SP,ACC和AUC，AUC的计算可以基于平台的软件包）。(. using BP neural network to design the classifier for male and female students. The features include height, weight, whether they like mathematics, whether they like literature, and whether they like sports. The BP neural network contains a hidden layer, and the number of hidden nodes is five (5). Requirements: self compiled code, post propagation algorithm, cross validation method to achieve performance evaluation (including SE, SP, ACC and AUC, AUC calculation can be based on platform software package).)