Probabilistic estimation of software development effort techniques using machine learning

  • Authors

    • Dr P. Vidya Sagar
    • Dr Nageswara Rao Moparthi
    • Venkata Naresh Mandhala
    https://doi.org/10.14419/ijet.v7i2.7.12233

    Received date: April 27, 2018

    Accepted date: April 27, 2018

    Published date: March 18, 2018

  • Software Effort, SVM, Artificial Neural Networks, Support Vector Machine, Accuracy

  • Abstract

    Precisely assessing programming exertion is likely the greatest test confronting for programming engineers. Assessments done at the prop-osition arrange has high level of incorrectness, where prerequisites for the degree are not characterized to the most reduced subtle elements, but rather as the venture advances and necessities are explained, exactness and certainty on appraise increments. It is vital to pick the correct programming exertion estimation systems for the forecast of programming exertion. Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been utilized on guarantee dataset for forecast of programming exertion in this article.

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  • How to Cite

    P. Vidya Sagar, D., Nageswara Rao Moparthi, D., & Naresh Mandhala, V. (2018). Probabilistic estimation of software development effort techniques using machine learning. International Journal of Engineering and Technology, 7(2.7), 1085-1090. https://doi.org/10.14419/ijet.v7i2.7.12233