Naïve Bayes classifiers are based on the class-conditional independence assumption, which means the following: a) the data samples in the training set are independent from the samples in the test set. b) There is no dependence relationship among the different samples in the data set. c) There is no dependence relationship among the attributes describing the data samples. d) The class labels are independent, that is not two class labels have a dependence relationship.