Banca de QUALIFICAÇÃO: Lucas Fonseca Gonçalez

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : Lucas Fonseca Gonçalez
DATE: 27/12/2023
TIME: 14:00
LOCAL: Remota
TITLE:

Machine Learning as a way to predict public works stoppages: A case study of Proinfância

KEY WORDS:

CRISP-DM; Risk Management; Educational Infrastructure; TEMAC; Machine Learning; Predictive Model; Public Works.

PAGES: 63
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUBÁREA: Metodologia e Técnicas da Computação
SPECIALTY: Sistemas de Informação
SUMMARY:

Educational infrastructure plays an important role in facilitating access to education, improving academic results, and reducing school dropout rates. However, Brazil faces a serious issue concerning public educational projects: a high rate of work stoppages. The overall objective of this study is to present steps to reduce the number of halted constructions. To achieve this, the CRISP-DM methodology will be used as a guide for creating a Machine Learning model that aims to predict projects with a higher risk of suspension. The model will use datasets from the National Fund for the Development of Education (FNDE) related to the Proinfância program.

COMMITTEE MEMBERS:
Presidente - 1114843 - ARI MELO MARIANO
Interno - ***.366.561-** - JOAO GABRIEL DE MORAES SOUZA - UnB
Externo à Instituição - DANIEL CAPALDO AMARAL - USP