Abstract
This paper will present a comprehensive overview of the use of fuzzy logic approach in modeling as a decision support tool for cost estimation. The model is based on expectation-maximisation (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models. The clusters given by the EM algorithm has lead to the development of fuzzy rules. The best fuzzy logic model was found to consist of two fuzzy rules. The result also indicates that kind of behavior given by the EM clustering algorithm has reduced the uncertainty of estimate, which in turn the accuracy of the estimate is improved.
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