RT Conference Proceedings
T1 Data mining for municipal financial distress prediction
A1 Alaminos Aguilera, David
A1 Fernández, David
A1 García-Lopera, Francisca
A1 Fernández, Manuel Ángel
K1 Minería de datos (Informática)
AB Data mining techniques are capable of extracting valuable knowledge from large and variable databases. This work proposes a data mining method for municipal financial distress prediction. Using a new proxy of municipal financial situation and a sample of 128 Spanish municipalities, the empirical experiment obtained satisfactory results, which testifies to the viability and validity of the data mining method proposed for municipal financial distress prediction.
YR 2018
FD 2018-07-31
LK https://hdl.handle.net/10630/16388
UL https://hdl.handle.net/10630/16388
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026