Can Neural Networks be easily Interpreted in Software Cost Estimation?

نویسندگان

  • Ali Idri
  • Taghi M. Khoshgoftaar
  • Alain Abran
چکیده

The use of the neural networks to estimate software development effort has been viewed with skepticism by the majority of the cost estimation community. Although, neural networks have shown their strengths in solving complex problems, their shortcoming of being ‘black boxes’ has prevented them to be accepted as a common practice for cost estimation. In this paper, we study the interpretation of cost estimation models based on a Back-propagation three multilayer Perceptron network. Our idea consists in the use of a method that maps this neural network to a fuzzy rule-based system. Consequently, if the obtained fuzzy rules are easily interpreted, the neural network will also be easy to interpret. Our experiment is made using the COCOMO’81 dataset.

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تاریخ انتشار 2002