International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 13 | Number 1 | Year 2014 | Article Id. IJCTT-V13P117 | DOI : https://doi.org/10.14445/22312803/IJCTT-V13P117

Performance Comparison of Data Mining Algorithms: A Case Study on Car Evaluation Dataset

Jamilu Awwalu , Anahita Ghazvini , Azuraliza Abu Bakar

Citation :

Jamilu Awwalu , Anahita Ghazvini , Azuraliza Abu Bakar, "Performance Comparison of Data Mining Algorithms: A Case Study on Car Evaluation Dataset," International Journal of Computer Trends and Technology (IJCTT), vol. 13, no. 1, pp. 78-82, 2014. Crossref, https://doi.org/10.14445/22312803/IJCTT-V13P117

Abstract

Cars are essentially part of our everyday lives. There are different types of cars as produced by different manufacturers; therefore the buyer has a choice to make. The choice buyers or drivers have mostly depends on the price, safety, and how luxurious or spacious the car is. Data mining tasks in terms of classification or prediction are applied in a variety of domains which includes manufacturing and business. But the choice of algorithm can be confusing because some algorithms are argued to have better performance record than others, depending on the associated task and nature of dataset. This study analyzes the performance of three data mining algorithms in terms of speed and accuracy on the car evaluation dataset obtained from the University of California Irvine (UCI) dataset.

Keywords

Data Mining, Decision Tree, Neural Network, Naive Bayesian.

References

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