Improving Sale Performance Prediction using Support Vector Machines Articles uri icon

publication date

  • May 2011

start page

  • 5129

end page

  • 5132

issue

  • 5

volume

  • 38

international standard serial number (ISSN)

  • 0957-4174

electronic international standard serial number (EISSN)

  • 1873-6793

abstract

  • In this article, an expert system based on support vector machines is developed to predict the sale performance of some insurance company candidates. The system predicts the performance of these candidates
    based on some scores, which are measurements of cognitive
    characteristics, personality, selling skills and biodata. An experiment
    is conducted to compare the accuracy of the proposed system with respect
    to previously reported systems which use discriminant functions or
    decision trees. Results show that the proposed system is able to improve
    the accuracy of a baseline linear discriminant based system by more
    than 10% and that also exceeds the state of the art systems by almost
    5%. The proposed approach can help to reduce considerably the direct and
    indirect expenses of the companies.