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Comparison of open source data mining softwares on a data set
Author(s) -
BAYKAL Abdullah,
C. Cengiz
Publication year - 2018
Publication title -
african journal of mathematics and computer science research
Language(s) - English
Resource type - Journals
ISSN - 2006-9731
DOI - 10.5897/ajmcsr2018.0669
Subject(s) - computer science , data mining , open source , data set , set (abstract data type) , open source software , data source , software , key (lock) , process (computing) , artificial intelligence , computer security , programming language , operating system
Data mining is the process of extracting informative and useful rules or relations, that can be used to make predictions about the values of new instances, from existing data. A wide range of commercial and open source software programs are used for data mining. In this study, a comparison of several classification algorithms included in some open source softwares such as WEKA, Tanagra and Scikit-learn using SEER (Survillance Epidemiology and End Results) data set which consists of 60948 instances is performed. Key words: Data mining, classification analysis, open source data mining tools.

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