Open AccessExperimental Evaluation of Open Source Data Mining Tools: R, Rapid Miner and KNIME
Author(s) -
Hemlata,
Preeti Gulia
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.a5341.119119
Subject(s) - computer science , decision tree , analytics , open source , data mining , data science , tree (set theory) , big data , software , operating system , mathematical analysis , mathematics
In the current scenario of Big Data, open source Data Mining tools are very popular in business data analytics. The paper presents a comprehensive study of three most popular open source data mining tools – R, RapidMiner and KNIME. The tools are compared by implementing them on two real datasets. Performance is evaluated by creating a decision tree of the datasets taken. Our objective is to find the best tool for classification. The study can help researchers, developers and users in selecting a tool for accuracy in their data analysis and prediction. Experiments depict that accuracy level of the tool changes with the quantity and quality of the dataset. The results show that RapidMiner is the best tool followed by KNIME and R