Ranking and Clustering of Software Cost Estimation Models
Vijaya Wable, Spurti Shinde, Marian Petre · 2014
In today's software industries there are many software cost estimation models are there to estimate the financial need to develop a software. The result of the models typically requires obtaining approval to proceed, and factored into business plans, budgets, and other financial planning and tracking mechanisms. Many of the models are providing irrelevant output thereby putting the organization in confusion. So to choose a perfect cost estimation model becomes higher priority for the companies. In our research to rank the cost estimation models proposed system uses previous performance data sets as the evidence. System uses correlation similarity and preference model to identify the rank of the model and thereby cluster the cost estimation models. In our proposed model we have taken many parameters to perform ranking and clustering. In this paper we are demonstrating abilities of software cost estimation method and clustering them; based on their features. It helps us to rank together for further usage of software.