Fit data selection for software effort estimation models
Koji Toda, Akito Monden, Kenichi Matsumoto · 2008
To construct a better multivariate regression model for software effort estimation, this paper proposes a method to select projects as a fit data from a given project data set based on estimation target's features. While regression models were often constructed from all available project data, this paper showed the necessity of fit data selection, and showed that the proposed method is one of the effective and systematic means to do the selection.