Comparative Study of the Performance of M5-Rules Algorithm with Different Algorithms


The effort invested in a software project is probably one of the most important and most analyzed variables in recent years in the process of project management. The determination of the value of this variable when initiating software projects allows us to plan adequately any forthcoming activities. As far as estimation and prediction is concerned there is still a number of unsolved problems and errors. To obtain good results it is essential to take into consideration any previous projects. Estimating the effort with a high grade of reliability is a problem which has not yet been solved and even the project manager has to deal with it since the beginning. In this study, performance of M5-Rules Algorithm, single conjunctive rule learner and decision table majority classifier are experimented for modeling of Effort Estimation of Software Projects and performance of developed models is compared with the existing algorithms namely Halstead, Walston-Felix, Bailey-Basili, Doty in terms of MAE and RMSE. The proposed techniques are run in the WEKA environment for building the model structure for software effort and the formulae of existing models are calculated in the MATLAB environment. The performance evaluation criteria are based on MAE and RMSE. The result shows that the M5-Rules have the best performance and can be used for the effort estimation of all types of software projects.

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H. Duggal and P. Singh, "Comparative Study of the Performance of M5-Rules Algorithm with Different Algorithms," Journal of Software Engineering and Applications, Vol. 5 No. 4, 2012, pp. 270-276. doi: 10.4236/jsea.2012.54032.

Conflicts of Interest

The authors declare no conflicts of interest.


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