R语言-朴素贝叶斯分类器（1）

利用给定的数据预测某天（"Sunny","Cool","High","Strong"）是否打球……

数据：

NO Outlook Temperature Humidity Wind Play
1 Sunny Hot High Weak No
2 Sunny Hot High Strong No
3 Overcast Hot High Weak Yes
4 Rain Mild High Weak Yes
5 Rain Cool Normal Weak Yes
6 Rain Cool Normal Strong No
7 Overcast Cool Normal Strong Yes
8 Sunny Mild High Weak No
9 Sunny Cool Normal Weak Yes
10 Rain Mild Normal Weak Yes
11 Sunny Mild Normal Strong Yes
12 Overcast Mild High Strong Yes
13 Overcast Hot Normal Weak Yes
14 Rain Mild High Strong No

代码：

data=read.table("C:\\code\\R\\playTennis.txt",header=T)
pre=c("Sunny","Cool","High","Strong","xx")
sum_Yes=length(which(data$Play=="Yes"))
sum_No=length(which(data$Play=="No"))
sum=sum_Yes+sum_No
#计算yes的概率
p_O_y=length(which(data$Outlook==pre[1]&data$Play=="Yes"))/sum_Yes
p_T_y=length(which(data$Temperature==pre[2]&data$Play=="Yes"))/sum_Yes
p_H_y=length(which(data$Humidity==pre[3]&data$Play=="Yes"))/sum_Yes
p_W_y=length(which(data$Wind==pre[4]&data$Play=="Yes"))/sum_Yes
p_y=(sum_Yes/sum)*p_O_y*p_T_y*p_H_y*p_W_y
#计算No的概率
p_O_n=length(which(data$Outlook==pre[1]&data$Play=="No"))/sum_No
p_T_n=length(which(data$Temperature==pre[2]&data$Play=="No"))/sum_No
p_H_n=length(which(data$Humidity==pre[3]&data$Play=="No"))/sum_No
p_W_n=length(which(data$Wind==pre[4]&data$Play=="No"))/sum_No
p_n=(sum_No/sum)*p_O_n*p_T_n*p_H_n*p_W_n
#结果
print(p_y)
print(p_n)

结果：

[1] 0.005291005
[1] 0.02057143

 

转载于:https://www.cnblogs.com/sklww/p/3507811.html