机器学习大作业之单变量朴素贝叶斯分类器

一开始用python写的，后来发现要延伸到二维的贝叶斯分类，然后想画一个二元正态分布图就很难....后来改用matlab

基础知识：Bayesian Principle:（查询书《模式分类》第二章

Task 1

According to the above principle and theory in section 2.2, design a Bayesian classifier for the classification of two classes of patterns which are subjected to Gaussian normal distribution and compile the corresponding programme codes.  

What we have: 1. two classes and the data in this two classes; 2. four loss paras 3.prior probability of two classes

    Teacher has given us the data ,the loss parameters and the prior probability. So we just need to calculate the P(x|wi) to get the P(wi|x). I decided to use the normal distribution to calculate the conditional probability(the parameters of the normal distribution were calculated according to the given data).  Here is my code:

import math
import matplotlib.pyplot as plt
import numpy as np

#'''This part