Evolutionary induced decision trees for dangerous software modules prediction

نویسندگان

  • Vili Podgorelec
  • Peter Kokol
چکیده

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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عنوان ژورنال:
  • Inf. Process. Lett.

دوره 82  شماره 

صفحات  -

تاریخ انتشار 2002