A SURVEY OF BAYESIAN NET MODELS FOR SOFTWARE DEVELOPMENT EFFORT PREDICTION
Łukasz Radliński · 2010
This paper discusses recent Bayesian nets built for software development effort prediction. Its aim is to bring closer these models as they may be competitive for other modeling techniques, especially for data-driven machine learning and statistical techniques. Each model has been briefly described and then analyzed in detail in terms of its main purpose, type of structure, data/knowledge base for building a model. Some models have been empirically validated for predictive accuracy and we discuss the results of this validation. The paper also discusses main problems related to building such models by domain experts.