TY  - JOUR
T1  - Rough Set Discretize Classification of Intrusion Detection System
AU - Sulaiman, Noor Suhana AU - Bakar, Rohani Abu 
JO  - Journal of Engineering and Applied Sciences
VL  - 11
IS  - 3
SP  - 488
EP  - 496
PY  - 2016
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2016.488.496
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2016.488.496
KW  - Rough set
KW  -equal frequency binning
KW  -discretization
KW  -classiffication
KW  -intrusion detection system
AB  - Many pattern classification tasks confront with the problem that may have a very high dimensional feature space like in Intrusion Detection System (IDS) data. Rough set is widely used in IDS to overcome the arising issue. In rough set, there are several stage processing including discretization part which is a vital task in data mining, particularly in the classification problem. Two results distinguish showing that the discretization stage is hugely important in both training and testing of IDS data. In proposed framework, analysis should been done to discretization, reduct and rules stage to determine the significant algorithm and core element in IDS data. The classification using standard voting, since it is a rule-based classification.
ER  -