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Title: GitHub - Escape-Li/bayes-python: 基于python的贝叶斯分类算法(数据集为Iris_data) · GitHub

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https://github.com/Escape-Li/bayes-python#bayes-python
https://github.com/Escape-Li/bayes-python#具体代码见bayes_irispy
https://github.com/Escape-Li/bayes-python#我直接用了iris_data数据集每种花我选取前45条数据当做训练集剩下5条数据另外存入测试集iris_test_data并将数据随机手动打乱
https://github.com/Escape-Li/bayes-python#测试集如下
https://github.com/Erikfather/bayes-python/blob/master/iris_test_data.jpg
https://github.com/Escape-Li/bayes-python#因为这个数据集是连续性属性所以需要利用概率密度函数
https://github.com/Escape-Li/bayes-python#具体实验步骤为
https://github.com/Escape-Li/bayes-python#1先读取数据集
https://github.com/Escape-Li/bayes-python#2计算训练数据集上每个类别的各个特征属性上的均值和方差
https://github.com/Escape-Li/bayes-python#3开始对测试数据集进行分类
https://github.com/Escape-Li/bayes-python#4首先估计先验概率这里我每个类别所占整体数据集的比例是一样的
https://github.com/Escape-Li/bayes-python#5利用概率密度函数计算测试数据集上各个属性在每个类别上的条件概率
https://github.com/Escape-Li/bayes-python#6计算后验概率先验概率条件概率
https://github.com/Escape-Li/bayes-python#7比较在各个类别上的后验概率取最大值则分为这个类别
https://github.com/Escape-Li/bayes-python#结果如下
https://github.com/Erikfather/bayes-python/blob/master/result.jpg
https://github.com/Escape-Li/bayes-python#我们将结果与测试集比较发现结果完全正确
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