Software Effort Estimation with Data Mining Techniques- A ReviewJournal: International Journal of Engineering Sciences & Research Technology (IJESRT) (Vol.3, No. 3)
Publication Date: 2014-03-30
Authors : Mohita Sharma; Neha Fotedar;
Page : 1646-1653
Keywords : Support vector machine; constructive Cost Model; K-Means; person- month; data mining.;
Effort Estimation is an important task in cost prediction of the software. This task comes under the planning phase of software project management. In this paper, a review of different data mining techniques used for effort estimation has been presented. The techniques taken into consideration are Clustered techniques (K-Means, K-NN-K-Nearest Neighbour), Regression techniques (MARS- Multivariate analysis for regression splines, OLS - Ordinary least square regression, SVR-Support vector regression, CART- classification and regression trees ) and classification techniques (SVM-Support vector machine, CBR-Case based reasoning). We can use the hybrid approach of these techniques for improving effort estimation.
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Last modified: 2014-06-17 22:00:53