NaiveBayes in R kann nicht vorhersagen

Question

Ich versuche, eine Klassifizierung mit NaiveBayes mit Iris DataSet mit e1071-Paket zu tun, und es stellt sich heraus, dass ich die Vorhersage nicht wie in Rpart machen kann. Wie kann ich das lösen, damit ich eine Verwirrungsmatrix basierend auf p4 erstellen kann, die ich vorherzusagen versuche?

> table(iris$Species) 

    setosa versicolor virginica 
     50   50   50 
> head(iris) 
    Sepal.Length Sepal.Width Petal.Length Petal.Width Species 
1   5.1   3.5   1.4   0.2 setosa 
2   4.9   3.0   1.4   0.2 setosa 
3   4.7   3.2   1.3   0.2 setosa 
4   4.6   3.1   1.5   0.2 setosa 
5   5.0   3.6   1.4   0.2 setosa 
6   5.4   3.9   1.7   0.4 setosa 
> set.seed(9850) 
> g<-runif(nrow(iris)) 
> irisr <- iris[order(g),] 
> m4 <- naiveBayes(Species~., data=irisr[1:100,], method="class") 
> m4 

Naive Bayes Classifier for Discrete Predictors 

Call: 
naiveBayes.default(x = X, y = Y, laplace = laplace, method = "class") 

A-priori probabilities: 
Y 
    setosa versicolor virginica 
     0.34  0.35  0.31 

Conditional probabilities: 
      Sepal.Length 
Y    [,1]  [,2] 
    setosa  5.000000 0.3797926 
    versicolor 5.857143 0.4545752 
    virginica 6.658065 0.7017949 

      Sepal.Width 
Y    [,1]  [,2] 
    setosa  3.461765 0.4221264 
    versicolor 2.717143 0.3212894 
    virginica 2.990323 0.3543584 

      Petal.Length 
Y    [,1]  [,2] 
    setosa  1.450000 0.1619016 
    versicolor 4.197143 0.4273624 
    virginica 5.600000 0.6066300 

      Petal.Width 
Y     [,1]  [,2] 
    setosa  0.2558824 0.1159707 
    versicolor 1.2800000 0.1827889 
    virginica 2.0000000 0.2708013 
> summary (m4) 
     Length Class Mode  
apriori 3  table numeric 
tables 4  -none- list  
levels 3  -none- character 
call 5  -none- call  
> p4<- predict(m4, irisr[101:150,], type="class") 
#Gives me this error ! How can I solve this ? 
Error in UseMethod("predict") : 
    no applicable method for 'predict' applied to an object of class "naiveBayes" 

Answer 1

Ich finde die Antwort!

> m4 <- naiveBayes(as.factor(Species)~., data=irisr[1:100,], method="class") 
> p4<-predict(m4, irisr[101:150,]) 
> p4 
[1] virginica setosa  versicolor virginica versicolor 
[6] setosa  setosa  versicolor versicolor versicolor 
[11] versicolor versicolor virginica setosa  versicolor 
[16] virginica virginica virginica versicolor virginica 
[21] setosa  virginica virginica setosa  virginica 
[26] setosa  setosa  versicolor setosa  versicolor 
[31] setosa  virginica virginica virginica setosa  
[36] virginica versicolor virginica setosa  setosa  
[41] virginica setosa  virginica virginica virginica 
[46] setosa  virginica virginica virginica setosa  
Levels: setosa versicolor virginica 
> table(irisr[101:150,5], predicted=p4) 
      predicted 
      setosa versicolor virginica 
    setosa   16   0   0 
    versicolor  0   11   4 
    virginica  0   1  18