Generating a Descriptive Model to Identify Military Personnel Incurring in Disciplinary Actions: A Case Study in the Ecuadorean Navy
The problem of navy personnel incurring in disciplinary actions has major consequences in the productivity and motivation of these individuals for getting the job done. Leaving it unsolved may negatively affect their careers, working environments, peers, families and in some cases the Navy’s reputation. The implementation of data mining is widely considered as a powerful instrument for acquiring new knowledge from a pile of historical data, which is normally left unstudied. The main purpose of this paper is to use a data-driven approach to generate a descriptive model aimed at discovering knowledge, insights and interesting patterns in the personnel misconduct. The results reveal promising insights, hence the reliability of this work as a decision making and decision support tool.
KeywordsData mining Exploratory data analysis Military offenses Disciplinary actions Personnel profile
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