Decision Tree, Naïve Bayes and Support Vector Machine Applying on Social Media Usage in NYC / Comparative Analysis
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Abstract
Data mining and classification are most research idea that used in many topics by researchers. This study presents the comparison of three algorithms for classifications such as (Decision Tree, Naïve Bayes and Support Vector Machine), applying for social media usage dataset by NYC, to get the best result of the classification algorithm that can classify the instances according to the platforms. The final result of this research refer to the Support Vector Machine returned the best result among these techniques.
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