Applied multivariate statistical analysis
Applied multivariate statistical analysis
C4.5: programs for machine learning
C4.5: programs for machine learning
Feature Selection via Discretization
IEEE Transactions on Knowledge and Data Engineering
On Changing Continuous Attributes into Ordered Discrete Attributes
EWSL '91 Proceedings of the European Working Session on Machine Learning
Concurrent Discretization of Multiple Attributes
PRICAI '98 Proceedings of the 5th Pacific Rim International Conference on Artificial Intelligence: Topics in Artificial Intelligence
Integrating in-process software defect prediction with association mining to discover defect pattern
Information and Software Technology
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A discretization technique converts continuous attribute values into discrete ones. Discretization is needed when classification algorithms require only discrete attributes. It is also useful to increase the speed and the accuracy of classification algorithms. This paper presents a dynamic discretization method, whose main characteristic is to detect interdependencies between all continuous attributes. Empirical evaluation on 12 datasets from the UCI repository shows that the proposed algorithm is a relatively effective method for discretization.