Improving Accuracy of Multiple Regression Analysis for Effort Prediction Model
Kazunori Iwata, Toyoshiro Nakashima, Yoshiyuki Anan, Naohiro Ishii · 2006
In this paper, we outline the effort prediction model and the evaluation experiment. In addition we explore the parameters in the model. The model predicts effort of embedded software developments via multiple regression analysis using the collaborative filtering. Because companies, recently, focus on methods to predict effort of projects, which prevent project failures such as exceeding deadline and cost, due to more complex embedded software, which brings the evolution of the performance and function enhancement. In the model, we have fixed two parameters named k and ampmax, which would influence the accuracy of predicting effort. Hence, we investigate a tendency of them in the model and find the optimum value