2026-06-01T19:50:01Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/163882026-02-03T12:01:18Zcom_10630_2254col_10630_37959

Alaminos Aguilera, David Fernández, David García-Lopera, Francisca Fernández, Manuel Ángel 2018-07-31T10:20:36Z 2018-07-31T10:20:36Z 2018-07-31 https://hdl.handle.net/10630/16388 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. eng open access Minería de datos (Informática) Data mining for municipal financial distress prediction conference output