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Case Based Reasoning and particularly Estimation by Analogy, has been used ina number of problem-solving areas, such as cost estimation. Conventionalmethods, despite the lack of a sound criterion for choosing nearest projects,were based on estimation using a fixed and predetermined number of neighborsfrom the entire set of historical instances. This approach puts boundaries tothe estimation ability of such algorithms, for they do not take intoconsideration that every project under estimation is unique and requiresdifferent handling. The notion of distributions of distances together with adistance metric for distributions help us to adapt the proposed method (we callit DD-EbA) each time to a specific case that is to be estimated without loosingin prediction power or computational cost. The results of this paper show thatthe proposed technique achieves the above idea in a very efficient way.

DD-EbA: An algorithm for determining the number of neighbors in cost estimation by analogy using distance distributions