Evolutionary induced decision trees for dangerous software modules prediction

doi:10.1016/S0020-0190(01)00284-8

Information Processing Letters

Volume 82, Issue 1, 15 April 2002, Pages 31-38

https://doi.org/10.1016/S0020-0190(01)00284-8 Get rights and content

Abstract

We study the possibility of constructing decision trees with evolutionary algorithms in order to increase their predictive accuracy. We present a self-adapting evolutionary algorithm for the induction of decision trees and describe the principle of decision making based on multiple evolutionary induced decision trees—decision forest. The developed model is used as a fault predictive approach to foresee dangerous software modules, which identification can largely enhance the reliability of software.

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Evolutionary induced decision trees for dangerous software modules prediction

Abstract

Internat. J. Medical Inform.

Decision trees based on automatic learning and their use in cardiology

J. Medical Systems

Spreadsheet software and decision making in nursing

Decision trees and decision making

IEEE Trans. System, Man Cybernetics

C4.5: Programs for Machine Learning

Evolutionary Algorithms in Theory and Practice