Efficiency comparison of Python and RapidMiner

Abstract

Machine learning is an important technique that helps companies, institutes, and humans to improve the quality of decision making. As there are many different free tools on the Internet for machine learning, we need comparisons, benchmarks to provide help in the selection of the appropriate analysis technique. This paper aims at providing a comparative study of the two most powerful and open-source machine learning tools Python and RapidMiner by using most common supervised machine learning techniques Decision Tree, Support Vector Machines, and Neural Networks on data analytic of PIMA Indian Diabetes Dataset and Mushroom Classification Dataset. The results reveal that the usage of RapidMiner provides better performance in terms of both accuracy and execution time.