Publications

Fault Forecasting Using Data-Driven Modeling: A Case Study for Metro do Porto Data Set

AuthID
P-00X-T4P

Author(s)

Editor(s)

Koprinska,I;Mignone,P;Guidotti,R;Jaroszewicz,S;Froning,H;Gullo,F;Ferreira,PM;Roqueiro,D;Ceddia,G;Nowaczyk,S;Gama,J;Ribeiro,R;Gavalda,R;Masciari,E;Ras,Z;Ritacco,E;Naretto,F;Theissler,A;Biecek,P;Verbeke,W;Schiele,G;Pernkopf,F;Blott,M;Bordino,I;Danesi,IL;Ponti,G;Severini,L;Appice,A;Andresini,G;Medeiros,I;Graca,G;Cooper,L;Ghazaleh,N;Richiardi,J;Saldana,D;Sechidis,K;Canakoglu,A;Pido,S;Pinoli,P;Bifet,A;Pashami,S

Document Type

Proceedings Paper

Year published

2023

Published

in MACHINE LEARNING AND PRINCIPLES AND PRACTICE OF KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2022, PT II in Communications in Computer and Information Science, ISSN: 1865-0929

Volume: 1753, Pages: 400-409 (10)

Conference

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (Ecml Pkdd), Date: SEP 19-23, 2022, Location: Grenoble, FRANCE

Indexing