This research paper is a comparative study of different clustering & classification algorithms. Clustering algorithms are compared on the basis of accuracy parameter, cluster distribution and time taken to build model. The six accuracy parameters for evaluating accuracy of classification algorithms are used. These parameters are TP rate, precision, recall, ROC area, f-measure and kappa statics. The four error measurement parameters for evaluating error rate of classification algorithms are considered i) RMSE (Root mean squared error) ii) MAE (Mean absolute error) iii) RRSE (Root relative squared error) iv) RAE(Relative absolute error).