We predict utility from New Zealand’s agricultural dataset ( with the Naive Bayes algorithm, particularly, we will group the eucalyptus dataset.

The utility has the values “none”, “low”, “average”, “good”, and “best”, so we need a classifier algorithm such as the Naive Bayes algorithm.

We choose it on Weka, we test the model using 10 folds cross-validation.

In summary, our model has an accuracy of 55.5707%.


The Naive Bayes algorithm will help us to classify utility using attributes, however, its accuracy is too low to be used in production or real-world environments, since it should be greater than 90%, it is acceptable.