A comparative study of attribute weighting heuristics for effort estimation by analogy

Abstract

Five heuristics for attribute weighting in analogy-based effort estimation are evaluated in this paper. The baseline heuristic involves using all attributes with equal weights. We propose four additional heuristics that use rough set analysis for attribute weighting. These five heuristics are evaluated over five data sets related to software projects. Three of the data sets are publicly available, hence allowing comparison with other methods. The results indicate that three of the rough set analysis based heuristics perform better than the equal weights heuristic. This evaluation is based on an integrated measure of accuracy.