Comparison of Prediction Success Performances for Classification Methods
Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 12
Abstract
Methods such as obtaining meaningful data from databases, applying preprocesses to data, classification of data, estimating classes of new data using existing data are important issues in data mining. In the classification techniques, it is aimed to find the most appropriate class information according to the predefined class information of the data compared to other data mining techniques, clustering and association rules. A correctly trained model will provide more accurate classification of new data. In this study, many classification methods such as Desicion Trees, Generilazed Linear Model, Navie Bayes, Random Forest have been used in the classification of car dataset and performance comparison of these methods has been made.
Authors and Affiliations
Ayşe Eldem
Keywords
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