Is my bayes classification right or meaningful? I have this dataset and I am learning about Bayes Classifier. After data cleaning, I have tried to use bayes classifier on it. I used R with this code:

library(klaR)
trainingChoco &lt;- chocolateApriori[1:707,]
testChoco &lt;- chocolateApriori[708:884,]
naivebayesChocolate &lt;- NaiveBayes(RatFactor ~ ., data=trainingChoco)
predictionChoco &lt;- predict(naivebayesChocolate, testChoco)
predictionChoco$posterior
library(caret)
tableChocolate &lt;- table(predictionChoco$class, testChoco$RatFactor)
confusionMatrix(tableChocolate)


Where RatFactor only has 1, 2, 3, 4, 5 as values (I rounded the ratings). This is my result:


  predictionChoco$posterior
                  1            2           3           4            5


1434 5.987980e-14 2.619121e-05 0.080559640 0.919414168 5.987980e-11

1435 4.205489e-10 8.759363e-03 0.022926453 0.968314183 4.205489e-10

1436 4.205489e-10 8.759363e-03 0.022926453 0.968314183 4.205489e-10

1439 1.004950e-10 4.709587e-03 0.006445339 0.988845074 1.004950e-10

1442 9.257687e-10 3.133371e-04 0.004947920 0.994738741 9.257687e-10

1443 3.260598e-13 8.227926e-03 0.171718690 0.820053058 3.260598e-07

[...]


  confusionMatrix(tableChocolate)


Confusion Matrix and Statistics

 1  2  3  4  5


1  0  0  0  0  0

2  0  2  5  7  0

3  0  7 42 28  0

4  0  5 45 36  0

5  0  0  0  0  0

Overall Statistics

           Accuracy : 0.452        

             95% CI : (0.3772, 0.5284)

No Information Rate : 0.5198     

P-Value [Acc &gt; NIR] : 0.97            

              Kappa : 0.0431          


Mcnemar's Test P-Value : NA              

Statistics by Class:

                 Class: 1 Class: 2 Class: 3 Class: 4 Class: 5


Sensitivity                NA   0.1429   0.4565   0.5070       NA

Specificity                 1   0.9264   0.5882   0.5283        1

Pos Pred Value             NA   0.1429   0.5455   0.4186       NA

Neg Pred Value             NA   0.9264   0.5000   0.6154       NA

Prevalence                  0   0.0791   0.5198   0.4011        0

Detection Rate              0   0.0113   0.2373   0.2034        0

Detection Prevalence        0   0.0791   0.4350   0.4859        0

Balanced Accuracy          NA   0.5346   0.5224   0.5177       NA

Do you think this result is right? Or am I missing something? Can you explain what would you understand by looking at this result please? Or can you post a similar example done step-by-step? Thanks.
Do you think this result is right?


Depends what you mean by "right"... the results seem reasonable, I don't see any obvious sign of mistake in the process.


  Can you explain what would you understand by looking at this result please? 


I observe that you don't have any data for classes 1 and 5, so technically it's a 3-classes problem. 


First with 3 classes the random baseline accuracy would be 0.33, 0.45 is better so your model does better than this (that's the bare minimum). 
However according to the confusion matrix class 3 has 92 instances out of a total of 172, which means that a basic majority class learner always predicting class 3 would get 52% accuracy (if my calculation is correct). So 45% is not very good.