Supervised Machine Learning Paradigms Approach for Predicting the Work Loyalty of Generation Z: Comparative Analysis - Agnieszka NIEMCZYNOWICZ; Piotr ARTIEMJEW; Joanna NIEŻURAWSKA-ZAJĄC (Communications of International Proceedings, 2021)
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)