Identifying Critical Factors in Case-Based Prediction

May 2004

Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2004)

Volume

Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2004)

All Papers

A reversible outcome is one that can be changed. For example, the failure of an ongoing project may be avoided if certain actions are taken, while an outcome such as the path of a hurricane cannot be changed under current knowledge. The major benefit of predicting reversible outcomes resides in the possibility to avoid unwanted results. For this purpose, it is necessary to identify contributing factors responsible for the outcome, which once modified, can steer the result to a desired outcome. Consequently, the incorporation of a method into a case-based reasoning system to identify contributing factors affecting an outcome can improve its usefulness. This paper compares different approaches, particularly the use of domain knowledge, with respect to their ability to identify sets of factors that reverse software development projects predicted to fail into a prediction of success.