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Naive Bayes Algoritma √?rneń?i Comparison of Open Source Data Mining Tools: Naive Bayes Algorithm Example


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Abstract


Data 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.

KeyWords
Data Mining, Classification Analysis, Naive Bayes.



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