Variable Ordering for Bayesian Networks Learning from Data

Classification is an important task in data mining processes. In this work, the χ test is used to define the order of the variables of a dataset to be used in Bayesian classification tasks. Two Bayesian classifiers are used to verify the influence of the variables ordering in the classification rate. The first one is based on the K2 algorithm which has strong dependency upon the initial order of the variables, and the second one is the algorithm used in BNPC software which is based on the conditional independence (CI) principle and doesn’t depend on an initial variables order. Four datasets (from UCI repository) are classified with and without the defined order and the results are compared.