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Many cost estimation models have been proposed over the last three decades.In this study, we investigate fuzzy ID3 decision tree as a method for softwareeffort estimation. Fuzzy ID software effort estimation model is designed byincorporating the principles of ID3 decision tree and the concepts of the fuzzysettheoretic; permitting the model to handle uncertain and imprecise data whenpresenting the software projects. MMRE (Mean Magnitude of Relative Error) andPred(l) (Prediction at level l) are used, as measures of prediction accuracy,for this study. A series of experiments is reported using ISBSG softwareprojects dataset. Fuzzy trees are grown using different fuzziness controlthresholds. Results showed that optimizing the fuzzy ID3 parameters can improvegreatly the accuracy of the generated software cost estimate.

Investigating Effort Prediction of Software Projects on the ISBSG Dataset