To achieve high accuracy while lowering false alarm rates are major challenges in designing an intrusion detection system. In addressing this issue, this paper proposes an ensembl...
Anazida Zainal, Mohd Aizaini Maarof, Siti Mariyam ...
Learning from noisy data is a challenging and reality issue for real-world data mining applications. Common practices include data cleansing, error detection and classifier ensemb...
Yan Zhang, Xingquan Zhu, Xindong Wu, Jeffrey P. Bo...
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
The use of bagging is explored to create an ensemble of fuzzy classifiers. The learning algorithm used was ANFIS (Adaptive Neuro-Fuzzy Inference Systems). We compare results from b...
Juana Canul-Reich, Larry Shoemaker, Lawrence O. Ha...