Scientific Publications

My publications on DBLP and my profile on Google Scholar.

2013

• Luis Torgo and Rita P. Ribeiro and Bernhard Pfahringer and Paula Branco : SMOTE for Regression
  in 16th Portuguese Conference on Artificial Intelligence, EPIA 2013, pp. 378-389. (c) Springer
  (Link to published manuscript) (Site with associated material to reproduce the work)
  

• Jan N. van Rijn and Bernd Bischl and Luis Torgo and Bo Gao and Venkatesh Umaashankar and Simon Fischer and Patrick Winter and Bernd Wiswedel and Michael R. Berthold and Joaquin Vanschoren : OpenML: A Collaborative Science Platform
  in Proceedings of ECML/PKDD'2013, pp. 645-649. Springer
  

  2012

• Ohashi,O. and Torgo,L. : Spatial Interpolation using Multiple Regression
  in ICDM 2012 - IEEE International Conference on Data Mining, pp. 1044--1049. (c) IEEE Computer Society
  (Link to published manuscript) (Site with associated material to reproduce the work)
  

• Ohashi,O. and Torgo,L. : Wind speed forecasting using spatio-temporal indicators
  in Proceedings of ECAI 2012 - 20th European Conference on Artificial Intelligence
  

• Drury,B., Torgo,L. and Almeida, J.J.: Classifying News Stories with a Constrained Learning Strategy to Estimate the Direction of a Market Index
  International Journal of Computer Science & Applications, vol. 9 - 1, pp. 1-22. Technomathematics Research Foundation, ISSN 0972-9038.
  

  2011

• Drury,B., Torgo,L. and Almeida, J.J.: Guided Self Training for Sentiment Classification
  in Proceedings of International Conference On Recent Advances in Natural Language Processing (RANLP 2011) - ROBUS workshop. Hissar, Bulgaria, September 12-14.
  

• Drury,B. and Dias,G. and Torgo,L. : Contextual Classification Strategy for Polarity Classification of Direct Quotations from Financial News
  in International Conference On Recent Advances in Natural Language Processing (RANLP 2011). Hissar, Bulgaria, September 12-14.
  

• Torgo,L. and Ohashi,O. : 2D-Interval Predictions for Time Series
  in Proceedings of 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2011)
  (Site with associated material to reproduce the work)

• Torgo,L. and Lopes,E. : Utility-based Fraud Detection
  in Proceedings of 22th International Joint Conference on Artificial Intelligence (IJCAI'2011), p. 1517-1522. AAAI Press.
  (Site with associated material to reproduce the work)

• Drury,B. and Torgo,L. and Almeida, J.J.: : Classifying News Stories to Estimate the Direction of a Stock Market Index
  in Proceedings of CISTI'2011
  

• Torgo,L. : Model Trees
  in Encyclopedia of Machine Learning, C.Sammut and G.I.Webb (Eds.). Pages 684--686, Springer, 2011. ISBN: 978-0-387-30768-8.
  

• Torgo,L. : Regression Trees
  in Encyclopedia of Machine Learning, C.Sammut and G.I.Webb (Eds.). Pages 842--845, Springer, 2011. ISBN: 978-0-387-30768-8.
  

  2010

• Torgo,L. : Data Mining with R: Learning with Case Studies
  CRC Press, 2010. ISBN: 9781439810187
  

• Torgo,L. and Soares,C.: Resource-bounded Outlier Detection Using Clustering Methods
  in Data Mining for Business Applications, C.Soares and R. Ghani (Eds.). Pages 84--98, IOS Press (2010). ISBN: 978-1607506324).
  

• Ohashi,O., Torgo,L. and Ribeiro,R. : Interval Forecast of Water Quality Parameters
  in ECAI 2010 - 19th European Conference on Artificial Intelligence, edited by H. Coelho, R. Studer and M. Wooldridge. Vol. 215, pp. 283-288. IOS Press. ISBN 978-1-60750-605-8
  

• Herrera,M.; Torgo,L.; Izquierdo,J. and Garcia, R.: Predictive models for forecasting hourly urban water demand
  Journal of Hydrology Volume 387, Issues 1-2, pp. 141-150. Elsevier.
  

  2009

• Torgo,L.: Detecção de Fraude usando o R: um caso de estudo
  in Boletim da Sociedade Portuguesa de Estatística. Outubro de 2009.

• Torgo,L. and Ribeiro,R. : Precision and Recall for Regression
  in Proceedings of the 12th International Conference on Discovery Science (DS'2009). LNAI - 5808. (c) Springer, 2009.
  

• Torgo,L. and Pereira,W. and Soares,C.: Detecting Errors in Foreign Trade Transactions: Dealing with Insufficient Data
  in 14th Portuguese Conference on Artificial Intelligence, EPIA 2009, Lopes, L. et. al (eds.). LNAI - 5816, (c) Springer, 2009
  

• Torgo,L. : A Linguagem R: programação para a análise de dados
  Escolar Editora. ISBN: 978-972-592-246-0
  

  2008

• Ribeiro,R., Torgo,L. : A Comparative Study on Predicting Algae Blooms in Douro River, Portugal
  Ecological Modelling vol.212 (1-2), pp. 86-91. Elsevier.
  

• Ribeiro,R., Torgo,L. : Utility-based performance measures for regression
  Proceedings of the 3rd Workshop on Evaluation Methods for Machine Learning, in conjunction with the 25th International Conference on Machine Learning (ICML 2008).
  

  2007

• Torgo,L.: Resource-bounded Fraud Detection
  in Progress in Artificial Intelligence, 13th Portuguese Conference on Artificial Intelligence, EPIA 2007, Neves et. al (eds.). LNAI 4874, pages 449-460. Springer
  

• Torgo,L., Ribeiro,R. : Utility-based Regression
  in Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases. Kok et. al (eds.) LNAI 4702, Springer
  

  2006

• Barbosa,J., Torgo,L. : Online ensembles for financial trading
  in Proceedings of the Workshop on Pratical Data Mining: applications, experiences and challenges, ECML/PKDD'2006. 2006.
  

• Ribeiro,R., Torgo,L. : Rule-based Prediction of Rare Extreme Values
  in Proceedings of the 9th International Conference on Discovery Science (DS'2006). Lecture Notes in Artificial Intelligence - 4265. (c) Springer, 2006.[BEST STUDENT PAPER AWARD]
  

• Silva,A., Jorge,A. and Torgo,L. : Design of an end-to-end method to extract information from tables
  International Journal on Document Analysis and Recognition, vol. 8 (2-3), p. 144-171. (c) Springer, 2006.
  

• Torgo,L., Ribeiro,R. : Predicting Rare Extreme Values
  in Proceedings of the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'2006). W. Ng et al. (eds.). Lecture Notes in Artificial Intelligence - 3918. (c) Springer, 2006.
  (extended Internal Report)
  

  2005

• Torgo,L., Marques,J. : Adapting Peepholing to Regression Trees
  in Proceedings of the 12th EPIA. (c) Springer, 2005.
  

• Torgo,L. : Regression Error Characteristic Surfaces
  in Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2005). Chicago, USA. (c) ACM, 2005.
  

• Torgo,L. : The TNT Financial Trading System: a midterm report
  in Proceedings of the Workshop on Data Mining for Business at ECML/PKDD 2005. Porto, Portugal, 2005.
  

• Ribeiro,R., Torgo,L. : A Comparative Study on Predicting Algae Blooms in River Douro, Portugal
  in Proceedings of the V European Conference on Ecological Modelling (ECEM-2005). Pushshino, Russia. 2005.
  

  2004

• Loureiro,A., Torgo,L., and Soares,C. : Outlier Detection using Clustering Methods: a data cleaning application
  in Proceedings of KDNet Symposium on Knowledge-based Systems for the Public Sector. Bonn, Germany.
  

  2003

• Silva,A., Jorge,A. and Torgo,L. : Selection of Table Areas for Information Extraction
  in Proceedings of the 3rd International Workshop in Document Analysis and its Applications (DLIA 2003).
  

• Silva,A., Jorge,A. and Torgo,L. : 564378 bytesAutomatic Selection of Table Areas in Documents for Information Extraction
  in Proceedings of Portuguese AI Conference (EPIA'03). Lecture Notes in Artificial Intelligence - 2902. (c) Springer-Verlag.
  

• Ribeiro,R. and Torgo,L. : Predicting Harmful Algae Blooms
  in Proceedings of Portuguese AI Conference (EPIA'03). Lecture Notes in Artificial Intelligence - 2902. (c) Springer-Verlag.
  

• Torgo,L., and Ribeiro,R.. : Predicting Outliers
  in Proceedings of Principles of Data Mining and Knowledge Discovery (PKDD'03). Lavrac,N. et al. (eds.). LNAI 2838, (c) Springer-Verlag.
  

• Torgo,L., and Pinto da Costa,J. : Clustered Partial Linear Regression
  in Machine Learning, 50 (3), pp. 303-319. Kluwer Academic Publishers.
  (Abstract)
  

  2002

• Hellstrom, T. and Torgo,L. : Post Processing Trading Signals for Improved Trading Performance
  in Data Mining III, A. Zanasi et. al (eds.), pp 437-447, Wit Press.
  (Abstract)
  

• Torgo,L. : Computationally Efficient Linear Regression Trees
  in Classification, Clustering and Data Analysis: recent advances and applications (Proceed. of IFCS 2002), Jajuga,K. et.al. (eds.). Studies in classification, data analysis, and knowledge organization. (c) Springer , 2002 .
  (Abstract)
  

  2001

• Torgo,L. : A study on end-cut preference in least squares regression trees
  in Proceedings of the Portuguese AI Conference (EPIA 2001), Brazdil,P. and Jorge,A. (eds.), LNAI 2258, (c) Springer-Verlag, 2001.
  (Abstract)
  

• Almeida,P. and Torgo,L. : The Use of Domain Knowledge in Feature Construction for Financial Time Series Prediction
  in Proceedings of the Portuguese AI Conference (EPIA 2001), Brazdil,P. and Jorge,A. (eds.), LNAI 2258, Springer-Verlag.
  

  2000

• Torgo,L. : Partial Linear Trees
  in Proceedings of the 17th International Conference on Machine Learning (ICML 2000). Langley,P. (ed.). Pages 1007-1014. Morgan Kaufmann Publishers, 2000.
  (Abstract)
  

• Torgo,L., and Pinto da Costa,J. : Clustered Partial Linear Regression
  in Proceedings of the Fifth International Workshop on Multistrategy Learning (MSL-2000), Guimar�es, Portugal, June, 2000.
  (Abstract)
  

• Torgo,L., and Pinto da Costa,J. : Clustered Partial Linear Regression
  in Proceedings of the 11th European Conference on Machine Learning (ECML 2000). Lopez de Mantaras,R. and Plaza,E. (eds.). LNAI 1810, p.426-436. (c) Springer-Verlag, 2000.
  (Abstract)
  

• Torgo,L., and Pinto da Costa,J. : Clustered Multivariate Regression
  in Data Analysis, Classification, and Related Methods. Kiers et al. (eds.). Studies in Classification, Data Analysis, and Knowledge Organization. (c) Springer-Verlag, 2000.
  (Abstract)
  

• Torgo,L. : Efficient and Comprehensible Local Regression
  in Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2000). Terano et al. (eds.). LNAI 1805, p. 376-379. (c) Springer-Verlag, 2000.
  (Abstract)
  (you may find a longer version of this work in this internal report, 66328 bytes in format ".ps.gz")
  

  1999

• Torgo,L. : Predicting the Density of Algae Communities using Local Regression Trees
  in Proceedings of the European Congress on Intelligent Techniques and Soft Computing (EUFIT'99)
  (invited paper as a consequence of the participation on the 3rd International ERUDIT Competition)
  (Abstract)
  

  1998

• Torgo,L. : A Comparative Study of Reliable Error Estimators for Pruning Regression Trees
  in Proceedings of the Iberoamericam Conference on AI (IBERAMIA-98) , Coelho,H. (ed.).
  (Abstract)(HTML version)
  

• Gama,J.; Torgo,L. and Soares,C. : Dynamic Discretization of Continuous Attributes
  in Proceedings of the Iberoamericam Conference on AI (IBERAMIA-98) , Coelho,H. (ed.).
  (Abstract)
  

• Torgo,L. : Error Estimates for Pruning Regression Trees
  in Proc. of the 10th European Conference on Machine Learning (ECML-98) , Nedellec,C. and Rouveirol,C. (eds.). LNAI 1398, Springer Verlag.
  (Abstract)
  

  1997

• Torgo,L. and Gama,J. : Regression using Classification Algorithms
  in Intelligent Data Analysis , Vol. 1, No. 4, http://www.elsevier.com/locate/ida.
  
  

• Torgo,L. : Functional Models for Regression Tree Leaves
  in Proceedings of the International Machine Learning Conference (ICML-97), Fisher,D.(ed.), Morgan Kaufmann Publishers.
  (Abstract)(HTML version)
  

• Torgo,L. and Gama,J. (1997) : Search-based Class Discretization
  in Proceedings of the European Conference on Machine Learning (ECML-97). Lecture Notes in Artificial Intelligence 1224, Springer Verlag. Prague, Czech Republic.
  (Abstract)(HTML version)
  

• Torgo,L.(1997) : Kernel Regression Trees
  Poster papers of the European Conference on Machine Learning (ECML-97), Internal Report of Faculty of Informatics and Statistics, University of Economics, Prague. ISBN:80-7079-368-6.
  

  1996

• Torgo,L. and Gama,J. (1996) : Regression by Classification
  in Proceedings of the Brasilian AI Symposium (SBIA'96), BorgesD., Kaestner,C.(eds.), Lecture Notes in Artificial Intelligence 1159, Springer Verlag. Curitiba, Brazil.
  (Abstract)(HTML version)
  

  1995

• Torgo,L. (1995) : Applying Propositional Learning to Time Series Prediction in Workshop on Statistics, Machine Learning and Knowledge Discovery in Databases edited by Kodratoff, Y. et. al, that took place at the European Conference on Machine Learning, ECML-95.
  (Abstract)(HTML version)
  

• Torgo,L. (1995) : Data Fitting with Rule-based Regression
  Proceedings of the workshop on Artificial Intelligence Techniques (AIT'95), Zizka,J. & Brazdil,P. (eds.), Brno, Czech Republic.
  (Abstract)(HTML version)
  

  1993

• Torgo,L. (1993) : Controlled Redundancy in Incremental Rule Learning in Proceedings of the European Conference on Machine Learning (ECML-93), Brazdil,P.(ed.), Lecture Notes in Artificial Intelligence 667, Springer Verlag.
  (Abstract) (HTML version)
  

• Torgo,L. (1993) : Rule Combination in Inductive Learning in Proceedings of the European Conference on Machine Learning (ECML-93), Brazdil,P.(ed.), Lecture Notes in Artificial Intelligence 667, Springer Verlag.
  (Abstract) (HTML version)
  

  1991

• Torgo,L.; Kubat,M. (1991) : Knowledge Integration and Forgetting in Proceedings of the Checoslovak AI Conference in 1991, Prague.
  (Abstract) (HTML version)
  

• Brazdil, P.; Gams, M.; Sian, S.; Torgo, L.; Van de Velde,W. (1991): Learning in Distributed Systems and Multi-Agent Environments, in Machine Learning: EWSL-91 (European Working Session on Learning), Y. Kodratoff (Ed.), Lecture Notes in Artificial Intelligence, Springer-Verlag
  (Abstract)(HTML version)
  

  1990

• Brazdil, P.; Torgo, L. (1990) : Knowledge Acquisition via Knowledge Integration, in Current Trends in Knowledge Acquisition, Wielinga, B. et al (eds.), IOS Press.
  (Abstract)