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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
In this study, Classfication Analysis comparisons were carried out over the car evaluation data set consisting of 1728 registers especially on Weka, Orange, KNIME and Tanagra as open source software tools.
📌 3 Key Takeaways
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Objective & Hypothesis:Data mining is to find correlations and rules which ensure meaningful and potentially useful estimations to be carried out for future among vast amount of existing data through computer programs.
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Key Findings & Data:Today, many commercial or open source software tools are used regarding this matter.
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Conclusion & Impact:In this study, Classfication Analysis comparisons were carried out over the car evaluation data set consisting of 1728 registers especially on Weka, Orange, KNIME and Tanagra as open source software tools.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Data Mining · Classfication Analysis · Open Source Data Mining Tools
Abstract
Data mining is to find correlations and rules which ensure meaningful and potentially useful estimations to be carried out for future among vast amount of existing data through computer programs. Today, many commercial or open source software tools are used regarding this matter. In this study, Classfication Analysis comparisons were carried out over the car evaluation data set consisting of 1728 registers especially on Weka, Orange, KNIME and Tanagra as open source software tools.
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Cite This Article
Baykal, A., Coşkun, C. (2018). PERFORMANCE ANALYSIS OF CLASSIFICATION ALGORITHMS OF SEVERAL DATA MINING SOFTWARES. Middle East Journal of Science, Volume: 4 Issue: 2. https://doi.org/10.23884/mejs.2018.4.2.06