Utilization of K-NN algorithm for expectation maximization based classification method

K nearest neighbor and Bayesian algorithms are effective methods of machine learning. In this work a data elimination approach is proposed to improve data clustering. The proposed method is based on hybridization of K nearest neighbor and Bayesian learning algorithms. The suggested method is tested on well-known machine learning data sets such as iris, wine and breast cancer and the results are concluded.