根据贝叶斯原理设计的一个简单的分类器，利用已知样本数据训练后，分类器就可以对未知样本进行分类。（实验时采用的是Iris数据集。）-According to the design of a simple Bayesian classifier, using the known training sample data, the classifier can classify the unknown samples. (Experiments using the Iris data set.)

用随机森林RF方法分类IRIS数据集，用一百个数据做训练集，五十个作为测试集，并统计出错误率，可直接运行-Classification method with random forests RF IRIS data set, using one hundred data to do training set, and fifty as a test set, and the statistical error rate, can be directly run