Variable precision rough set model
Journal of Computer and System Sciences
Feature Selection via Discretization
IEEE Transactions on Knowledge and Data Engineering
A Modified Chi2 Algorithm for Discretization
IEEE Transactions on Knowledge and Data Engineering
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
VPRSM Approach to WEB Searching
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
A discretization method for rough sets theory
Intelligent Data Analysis
A Modified Chi2 Algorithm Based on the Significance of Attribute
WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology
Topological approaches to covering rough sets
Information Sciences: an International Journal
On Three Types of Covering-Based Rough Sets
IEEE Transactions on Knowledge and Data Engineering
A discretization algorithm based on Class-Attribute Contingency Coefficient
Information Sciences: an International Journal
A bottom-up approach to discover transition rules of cellular automata using ant intelligence
International Journal of Geographical Information Science
Control approach to rough set reduction
Computers & Mathematics with Applications
Ameva: An autonomous discretization algorithm
Expert Systems with Applications: An International Journal
Reduction about approximation spaces of covering generalized rough sets
International Journal of Approximate Reasoning
A novel Chi2 algorithm for discretization of continuous attributes
APWeb'08 Proceedings of the 10th Asia-Pacific web conference on Progress in WWW research and development
A discretization algorithm for uncertain data
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
Covering based approximation – a new type approach
International Journal of Computational Vision and Robotics
An effective discretization based on Class-Attribute Coherence Maximization
Pattern Recognition Letters
Binary relation based rough sets
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
UniDis: a universal discretization technique
Journal of Intelligent Information Systems
Toward an efficient and scalable feature selection approach for internet traffic classification
Computer Networks: The International Journal of Computer and Telecommunications Networking
Compact classification of optimized Boolean reasoning with Particle Swarm Optimization
Intelligent Data Analysis
A biological continuum based approach for efficient clinical classification
Journal of Biomedical Informatics
Hi-index | 0.00 |
The Variable Precision Rough Sets (VPRS) model is a powerful tool for data mining, as it has been widely applied to acquire knowledge. Despite its diverse applications in many domains, the VPRS model unfortunately cannot be applied to real-world classification tasks involving continuous attributes. This requires a discretization method to preprocess the data. Discretization is an effective technique to deal with continuous attributes for data mining, especially for the classification problem. The modified Chi2 algorithm is one of the modifications to the Chi2 algorithm, replacing the inconsistency check in the Chi2 algorithm by using the quality of approximation, coined from the Rough Sets Theory (RST), in which it takes into account the effect of degrees of freedom. However, the classification with a controlled degree of uncertainty, or a misclassification error, is outside the realm of RST. This algorithm also ignores the effect of variance in the two merged intervals. In this study, we propose a new algorithm, named the extended Chi2 algorithm, to overcome these two drawbacks. By running the software of See5, our proposed algorithm possesses a better performance than the original and modified Chi2 algorithms.