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Neural networks are often selected as tool for software effort prediction because of their capability to approximate any continuous function with arbitrary accuracy. A major drawback of neural networks is the complex mapping between inputs and output, which is not easily understood by a user. This paper describes a rule extraction technique that derives a set of comprehensible IF-THEN rules from a...
Support vector machines (SVMs) are currently state-of-the-art for the classification task and, generally speaking, exhibit good predictive performance due to their ability to model nonlinearities. However, their strength is also their main weakness, as the generated nonlinear models are typically regarded as incomprehensible black-box models. In this paper, we propose a new active learning-based approach...
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