R 使用预测和朴素贝叶斯。能够计算条件概率,但产生完全错误的预测概率
我试图预测在新数据下是否玩:R 使用预测和朴素贝叶斯。能够计算条件概率,但产生完全错误的预测概率,r,probability,naivebayes,R,Probability,Naivebayes,我试图预测在新数据下是否玩: m <- NaiveBayes(as.factor(play)~ ., data=train) weather Temp humidity wind play fine hot high none no fine hot high few no cloud hot high none yes rain
m <- NaiveBayes(as.factor(play)~ ., data=train)
weather Temp humidity wind play
fine hot high none no
fine hot high few no
cloud hot high none yes
rain warm high none yes
rain cold medium none yes
rain cold medium few no
cloud cold medium few yes
fine warm high none no
fine cold medium none yes
我也试过了
m <- NaiveBayes(as.factor(train)~ ., data=train.play)
m这是一个拼写错误。你能解释一下为什么你认为结果是错误的吗?你的问题中没有问题。这是一个相对简单的问题,我手工计算了概率,得到:是的:0.01067你忘记了分母,所以你给出的实际上不是概率。只有将0.01067与No的分子进行比较才有意义,这里的分子是0,因为在“云”天气下,你没有观察到任何“No”。
$class
[1] yes
Levels: no yes
$posterior
no yes
[1,] 0.004836495 0.9951635
m <- NaiveBayes(as.factor(train)~ ., data=train.play)