One of the main reasons for choosing ARC is for its superior ability at handling imbalanced class distributions. It utilizes the association rule mining, making sampling unnecessary in many cases otherwise requiring sampling. In [WZYY05], ARC has been shown to produce the best result among many algorithms on the data set used for KDD- 98 [Kdd98], which has a skewed class distribution. In addition, ARC can handle high dimensionality (the data set has more than 400 variables) without a considerably long running time. Yet another significant advantage of ARC lies in the expressiveness of the model constructed. Each.
