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Recruitment Data Analysis Using Machine Learning in R Studio

  • R. DevakunchariEmail author
  • Niketha Anand
  • Anusha Vedhanayaki
  • Y. J. Visishta
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 98)

Abstract

Job classification is a system used to divide all jobs within a company and put them on a different regulated scale based on the overall work, salary level, skills, and commitment associated with a clear cut job. This likewise encourages organizations to look at similar jobs in various organizations inside their industry. Since the knowledge base is huge, it is difficult to physically identify the errors. Therefore, two machine learning algorithms namely Support Vector Machine and Random Forest are used to calculate the error percentage. The algorithm with the least error percentage is implemented to recruit employees. Our analysis overall shows that the random forest is more efficient than SVM.

Keywords

Support Vector Machine Multi class classification Random forest R studio Machine learning 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • R. Devakunchari
    • 1
    Email author
  • Niketha Anand
    • 1
  • Anusha Vedhanayaki
    • 1
  • Y. J. Visishta
    • 1
  1. 1.Department of Computer Science EngineeringSRMISTChennaiIndia

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