Software Development Effort Estimation Using Ensemble Machine Learning
International journal of computing, communication and instrumentation engineering · 2017
In software engineering, the main aim is to develop a high quality project that fall within scheduled time and budget, this procedure is called effort estimation.Effort estimation is crucial and important for a company to do because hiring more people than needed will lead to loss of income, and hiring less people than needed will lead to delay of project delivery.The aim of this study is to estimate software effort objectively by using machine learning techniques instead of subjective and time consuming estimation methods.Models using two machine learning techniques which are Support Vector Machine (SVM) and K-Nearest Neighbor (k-NN) separately and combining those together using ensemble learning were tried on two public datasets namely Desharnais and Maxwell.Results show that svm technique outperform k-nn technique, also ensemble learning improves the results.