Software Development Life Time Prediction Using Machine Learning Approach and There Comparison

Abstract

Software Engineering Project Management (SEPM) contributes to being a key factor in determining the success of a software project. One of the major tasks assigned to it is to estimate the time that needs to be put in the process of development of the software. In real life, we use a plethora of different prediction machine learning algorithms in order to calculate the time it takes, but we have to keep in mind the accuracy and performance of this algorithm. To get the comparative study of the different machine learning techniques that is simple linear-regression, multiple-regressions, Artificial neural networks and the Gaussian-algorithm will be put into action in an attempt to correctly calculate the time it takes in software production keeping in mind the parameters. The dataset that we are trending to test is the content of past software development. Eventually the results that we obtained are published.