1． 用 dataset1.txt 作为训练样本，用dataset2.txt 作为测试样本，采用身高和体重数据为特征，在正态分布假设下估计概率密度（只用训练样本），建立最小错误率贝叶斯分类器，写出所用的密度估计方法和得到的决策规则，将该分类器分别应用到训练集和测试集，考察训练错误率和测试错误率。将分类器应用到dataset3 上，考察测试错误率的情况。(1. using dataset1.txt as training samples as test samples by dataset2.txt, the height and weight data for feature in probability density estimation of normal distribution assumption (only training samples), the establishment of minimum error rate Bias classifier, write for density estimation method and get the decision rules, the classifiers are applied to training to investigate the training set and test set, error rate and error rate test. The classifier is applied to dataset3 to investigate the error rate of the test.)