An analysis of multi-objective evolutionary algorithms for training ensemble models based on different performance measures in software effort estimation
Leandro Lei Minku, Xin Yao · 2013
Background: Previous work showed that Multi-objective Evolutionary Algorithms (MOEAs) can be used for training ensembles of learning machines for Software Effort Estimation (SEE) by optimising different performance measures concurrently. Optimisation based on three measures (LSD, MMRE and PRED(25)) was analysed and led to promising results in terms of performance on these and other measures.