C4.5: programs for machine learning
C4.5: programs for machine learning
Discretization: An Enabling Technique
Data Mining and Knowledge Discovery
Boolean Reasoning for Feature Extraction Problems
ISMIS '97 Proceedings of the 10th International Symposium on Foundations of Intelligent Systems
Chi2: Feature Selection and Discretization of Numeric Attributes
TAI '95 Proceedings of the Seventh International Conference on Tools with Artificial Intelligence
IEEE Transactions on Knowledge and Data Engineering
An empirical investigation of the impact of discretization on common data distributions
Design and application of hybrid intelligent systems
An Extended Chi2 Algorithm for Discretization of Real Value Attributes
IEEE Transactions on Knowledge and Data Engineering
Feature selection based on rough sets and particle swarm optimization
Pattern Recognition Letters
Study on Discretization in Rough Set Via Modified Quantum Genetic Algorithm
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Rough Granular Computing in Knowledge Discovery and Data Mining
Rough Granular Computing in Knowledge Discovery and Data Mining
KEEL: a software tool to assess evolutionary algorithms for data mining problems
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Evolutionary and Metaheuristics based Data Mining (EMBDM); Guest Editors: José A. Gámez, María J. del Jesús, José M. Puerta
Recognition of multi-interval rules in dataset with continuous-valued attributes
Expert Systems with Applications: An International Journal
Ameva: An autonomous discretization algorithm
Expert Systems with Applications: An International Journal
Data discretization unification
Knowledge and Information Systems
Evolutionary Approach to Data Discretization for Rough Sets Theory
Fundamenta Informaticae
An Extended Comparison of Six Approaches to Discretization - A Rough Set Approach
Fundamenta Informaticae - Fundamentals of Knowledge Technology
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
Feature selection using rough-DPSO in anomaly intrusion detection
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
Feature selection with Intelligent Dynamic Swarm and Rough Set
Expert Systems with Applications: An International Journal
Discretization of continuous attributes in rough set theory and its application
CIS'04 Proceedings of the First international conference on Computational and Information Science
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Conventional cut selection in Boolean reasoning BR based discretization often produces under-optimistic prime cuts. This is due to the linearity of traditional heuristics in tackling high-dimensional space problem. We proposed a flexible yet compact and holistic solution by incorporating Particle Swarm Optimization PSO into the existing framework. The first challenge is to downsize the search space such that the probability of finding the global optimum is increased. The second task is to reconstruct the present fitness function so as to improve the classification performance of the induction algorithm, which in this case, C4.5. By injecting a filtration phase prior to the cut selection and introducing a tertiary term to the fitness function, the proposed extended BR with PSO EBRPSO discretizer is developed. Based on the evaluation using four real-world datasets i.e.: Heart, Breast, Iris and Wine, it is proven that EBRPSO outperforms the existing discretizers in terms of classification accuracy as well as reduction of the decision rules.