Discretization method based on binary ant colony and variable precision rough set

2019 2nd International Conference on Advanced Materials, Intelligent Manufacturing and Automation

Song, Jian^1 ; Jiang, Yu^1 ; Li, Dong^1 ; Bao, Yangwanying^1

College of Software Engineering, Chengdu University of Information Technology, Chengdu, Sichuan

610225, China^1

关键词: Approximation classification;    Data preprocessing;    Discretization algorithms;    Discretization method;    Discretizations;    Fitness functions;    Knowledge analysis;    Variable precision rough sets;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/569/5/052027/pdf
DOI  :  10.1088/1757-899X/569/5/052027

来源: IOP

【 摘 要 】

Discretization plays an important role in data pre-processing and has been used in fields such as artificial intelligence and data mining. A new discretization algorithm based on binary ant colony and variable precision rough set is proposed in this paper. Binary ant network is first built using candidate breakpoints, then global optimal breakpoints is searched in the network. The fitness function is established by the number of breakpoints and approximation classification accuracy of variable precision rough set. This method is compared with other algorithms using C4.5 classifier on the WEKA (Waikato Environment for Knowledge Analysis) platform and seven UCI data sets. The results indicate that the proposed method performs well.