Changing the Dynamics of Training by Predictive Modeling

Abstract

Predictive models using Support Vector Machines or Decision Tree Classifiers can be used in evaluating and advising students for the selection/placement process in the most suitable programs compatible with students’ aptitude. However, after the selection or placement process, one can go one step further by using predictive models in monitoring and evaluating the performance of trainees (students) through Machine Learning and Complex Adaptive Systems. In light of the monitoring and evaluation data, trainers can give corrective action, which may be necessary to ensure the optimal results during the ongoing training process. In the corporate sector, organizations can use the same methodology for training and evaluating their employees to meet their organizational objectives in the most effective way.