Banca de DEFESA: Marcella Guarnieri Mercês

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : Marcella Guarnieri Mercês
DATE: 22/06/2023
TIME: 14:00
LOCAL: Teams
TITLE:

Employee turnover prediction for military officers in the Brazilian Army using machine learning techniques

KEY WORDS:

Employee Churn, Classification, Machine Learning, Churn Prediction

PAGES: 45
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUMMARY:

This research aims to analyse the turnover of Brazilian Army’s officers over the years and propose a set of techniques that allow the identification of those officers more likely to resign. This result can help the Brazilian Army to act so that these resignations have a lesser impact in it’s productivity. The aproaches chosen considered the most common techniques used to predict employee churn in other areas. Common classification algorithms, such as K Nearest Neighbors (KNN), Naive Bayes, Suport Vector Machines (SVM), Decision Trees and Random Forest were used. Techniques that could improve the first results found were also studied so that they can be applied in the continuation of this research.

BANKING MEMBERS:
Interno - 1072256 - EDISON ISHIKAWA
Presidente - 1146571 - MARCIO DE CARVALHO VICTORINO
Externa à Instituição - MARIA CLÁUDIA REIS CAVALCANTI - IME
Interno - 1821656 - THIAGO DE PAULO FALEIROS