Naive Bayesian classification algorithm based onattribute clustering under different classification
Liu Qiong-sun · Journal of Computer Applications · 2011
In numerous classification methods,although Naive Bayesian(NB) classification algorithm is simple and effective,its attribute independence assumption ignores the correlation among attributes.To consider the influence of the attribute independence assumption,a new grouping technology which clusters the conditional attributes was proposed.This technology not only overcomes the deficiency arising from the attribute independence assumption of the traditional NB classification algorithm,but also reflects the different correlation intensity among attributes when the classification is different.Simulation results on a variety of UCI data sets illustrate the efficiency of this method.