Expectation Maximization (EM) is a widely employed mixture model-based data clustering algorithm and produces exceptionally good results. However, many researchers reported that the EM algorithm requires huge computational efforts than other clustering algorithms. This paper presents an...

Semi-supervised classification can help to improve generative classifiers by taking into account the information provided by the unlabeled data points, especially when there are far more unlabeled data than labeled data. The aim is to select a generative classification model using both unlabeled...