Comparison of open source data mining tools: Naive Bayes algorithm example

2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019 -- 24 April 2019 through 26 April 2019 -- -- 148870Data Mining is a set of processes that use many disciplines together in the process of analyzing large data. It is the concept of data mining that combines computer technologies, statistical analysis techniques, database technologies and many disciplines. There are many commercial and open source programs to implement Data Mining applications. In this study, open source data mining programs WEKA, Orange, Knime is described. A sample is analyzed with the classification algorithm in all of these programs. In this study, it was aimed to determine the difference between these 3 open source Data Mining programs with Naive Bayes classification algorithm by taking Bay iris, breast cancer, wine, monk, balance es data sets from UCI Machine Learning Repository database. With this study, there are suggestions for making comparisons according to the outputs from the programs. © 2019 IEEE.2-s2.0-8506857891