A Comparative Study of Data Mining Tools

Abstract

This Master’s thesis presents a comparative study of four popular free data mining tools: RapidMiner, Weka, KANIME, and Orange. The study evaluates their features, user-friendliness, performance, and community support. It examines data preparation, clustering and classification, and performs static and dynamic studies on various datasets. The study also assesses the integration and expansion capabilities of each tool. The results show significant disparities in performance and usefulness, with RapidMiner and Weka showing strong performance in managing large datasets and complex tasks. KANIME and Orange, on the other hand, offer intuitive interfaces and seamless connectivity with other data mining tools. This study provides valuable insights for data scientists, researchers, and practitioners in choosing the best data mining technology for their needs. By understanding each tool’s unique characteristics and constraints, users can make informed choices that enhance their data analysis processes and support evidence