Comparing performances of Markov Blanket and Tree Augmented Naïve-Bayes on the IRIS dataset

This research investigates the performances of the Markov Blanket (MB) and Tree Augmented Naïve-Bayes Network (TAN) of the Bayesian Network structure of the IRIS dataset. For evaluation purposes, the performances of the TAN, and MB classifiers were measured using statistical indices. Experimental results strongly suggested that the TAN is better than MB on training dataset and vise vasa in the test dataset. In the other hand, time computational complexity of both the classifiers was found to be equal. The result obtained in this research is of significance to researchers intending to use Bayesian Network to create a classifier for enhancing the performance of biometrics system