@article{niemczynowicz2021supervised,
  title = {Supervised Machine Learning Paradigms Approach for Predicting the Work Loyalty of Generation Z: Comparative Analysis},
  author = {Agnieszka NIEMCZYNOWICZ and Piotr ARTIEMJEW and Joanna NIEŻURAWSKA-ZAJĄC},
  year = 2021,
  url = {https://ibimapublishing.com/p-articles/37AI/2021/3789821/},
  journal = {Communications of International Proceedings},
  volume = 2021 (8),
  abstract = {In this paper, we are referring to the accuracy of behavioural prediction of  the level of loyalty of the Z generation group of employees based on the traditional employee motivation system. As an input, we use survey data. A Monte Carlo Cross Validation technique is used to validate prediction level. We used a range of popular classification techniques for testing, including Support Vector Machine (SVM), k-Nearest Neighbors algorithm (kNN), naive bayes, decision tree, random forests and discretized logistic regression.},
  keywords = {worker loyalty; Generation Z; Artificial Intelligence (AI); Support Vector Machine (SVM); k-Nearest Neighbors algorithm (kNN);},
  note = Article ID: 3789821
}