In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the known learning algorithms used are Naïve Bayesian (NB) and SMO (Self-Minimal-Optimisation) .Thus the following two learning algorithms are used on a Car review database and thus a model is hence created which predicts the characteristic of a review comment after getting trained. It was found that model successfully predicted correctly about the review comments after getting trained. Also two clustering algorithms: K-Means and Self Organising Maps (SOM) are used and worked upon a Car Database (which contains the properties of many different CARS), and thus the following two results are then compared. It was found that K-Means algorithm formed better clusters on the same data set.