Empirical Study to Suggest Optimal Classification Techniques for Given Dataset Problem statement: Classification techniques play an important role in Data Mining. Large number of classification techniques has been proposed in the literature. No single algorithm can be considered optimal for all type of data set. Accuracy of classification result highly depends on the selection of classification algorithms. Different classification techniques produce different results for the same data set. Thus finding the optimal algorithm for the given data set is a challenge. The outcome of this research work can be useful in selecting most suitable classifier for the given dataset. Research Methodology: To determine the effectiveness of various classification algorithms, authors run some well-known classification algorithms against some standard datasets. Effectiveness of various algorithms is measured on the basis of average accuracy, time taken to build classification model, mean absolute error etc. Results: Based on the comparative study of the experiment results, authors suggest the optimal algorithm for different categories of datasets.