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