Traditional statistical analyses need the a priori selection of a model best suited with the examine data established. Additionally, only substantial or theoretically pertinent variables according to prior experience are incorporated for analysis.Semi-supervised learning works by using equally unlabeled and labeled data sets to coach algorithms. No