On changing continuous attributes into ordered discrete attributes
EWSL-91 Proceedings of the European working session on learning on Machine learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Variable precision rough set model
Journal of Computer and System Sciences
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Machine Learning
Class-Driven Statistical Discretization of Continuous Attributes (Extended Abstract)
ECML '95 Proceedings of the 8th European Conference on Machine Learning
BNCOD 14 Proceedings of the 14th British National Conference on Databases: Advances in Databases
Data Mining using MLC++, A Machine Learning Library in C++
ICTAI '96 Proceedings of the 8th International Conference on Tools with Artificial Intelligence
Rough Set Analysis for Sudan School Certificate
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
Hi-index | 0.00 |
This paper presents application of Rough Sets algorithms to prediction of component failures in aerospace domain. To achieve this we first introduce a data preprocessing approach that consists of case selection, data labeling and attribute reduction. We also introduce a weight function to represent the importance of predictions as a function of time before the actual failure. We then build several models using rough set algorithms and reduce these models through a postprocessing phase. End results for failure prediction of a specific aircraft component are presented.