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V Cerqueira, L Torgo, C Soares (2021). Model Selection for Time Series Forecasting: Empirical Analysis of Different Estimators. arXiv.

V Cerqueira, L Torgo, C Soares, A Bifet (2021). Model Compression for Dynamic Forecast Combination. arXiv.

Mariana Oliveira, Luís Torgo, Vítor Santos Costa (2021). Evaluation procedures for forecasting with spatiotemporal data. Mathematics.

MM Alam, L Torgo, A Bifet (2021). A Survey on Spatio-temporal Data Analytics Systems. arXiv.

mohammad, Zahra Etemad, Amilcar Soares, Vania Bogorny, Stan Matwin, Luis Torgo (2020). Wise Sliding Window Segmentation: A classification-aided approach for trajectory segmentation. arXiv.

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Maria Monteiro, Mafalda S. Baptista, Joana Séneca, Luis Torgo, Charles K. Lee, S. Craig Cary, Catarina Magalhães (2020). Understanding the Response of Nitrifying Communities to Disturbance in the McMurdo Dry Valleys, Antarctica. Microorganisms.

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Inês Areosa, Luis Torgo (2019). Visual Interpretation of Regression Error. Progress in Artificial Intelligence.

Colin Bellinger, Paula Branco, Luis Torgo (2019). The CURE for Class Imbalance. Discovery Science.

Paula Branco, Luis Torgo, Rita P. Ribeiro (2019). Pre-processing approaches for imbalanced distributions in regression. Neurocomputing.

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Mohammad Etemad, Amilcar Soares, Stan Matwin, Luis Torgo (2019). On Feature Selection and Evaluation of Transportation Mode Prediction Strategies. Proceedings of the Workshops of the EDBT/ICDT 2019 Joint Conference, EDBT/ICDT 2019, Lisbon, Portugal, March 26, 2019.

Vitor Cerqueira, Luis Torgo, Carlos Soares (2019). Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters. arXiv.

Vitor Cerqueira, Luis Torgo, Carlos Soares (2019). Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes. Discovery Science.

I. Areosa, L. Torgo (2019). Explaining the Performance of Black Box Regression Models. 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Vitor Cerqueira, Luis Torgo, Igor Mozetic (2019). Evaluating time series forecasting models: An empirical study on performance estimation methods. arXiv.

António Gaspar G de Sousa, Maria Paola Tomasino, Pedro Duarte, Mar Fernández-Méndez, Philipp Assmy, Hugo Ribeiro, Jaroslaw Surkont, Ricardo B Leite, José B Pereira-Leal, Luis Torgo, Catarina Magalhães (2019). Diversity and Composition of Pelagic Prokaryotic and Protist Communities in a Thin Arctic Sea-Ice Regime. Microbial ecology.

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M. Oliveira, N. Moniz, L. Torgo, V. Santos Costa (2019). Biased Resampling Strategies for Imbalanced Spatio-Temporal Forecasting. 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

vitor, Luis Torgo, F. Pinto, C. Soares (2019). Arbitrage of Forecasting Experts. Machine Learning.

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P. Branco, L. Torgo (2019). A Study on the Impact of Data Characteristics in Imbalanced Regression Tasks. 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Paula Branco, Luis Torgo, Rita P. Ribeiro (2018). Resampling with neighbourhood bias on imbalanced domains. Expert Systems.

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Paula Branco, Luís Torgo, Rita P. Ribeiro (2018). REBAGG: REsampled BAGGing for Imbalanced Regression. Proceedings of Machine Learning Research (PMLR).

H. Ribeiro, T. de Sousa, J. Santos, A. Sousa, C. Teixeira, M. Monteiro, P. Salgado, A. Mucha, C. Almeida, L. Torgo, C. Magalhães (2018). Potential of dissimilatory nitrate reduction pathways in polycyclic aromatic hydrocarbon degradation. Chemosphere.

P. Branco, L. Torgo, R. Ribeiro (2018). MetaUtil: Meta Learning for Utility Maximization in Regression. Proceedings of the International Conference on Discovery Science, DS’18.

Mariana Oliveira, Luis Torgo, Vitor Santos Costa (2018). Evaluation procedures for forecasting with spatio-temporal data. Proceedings of the ECML/PKDD’2018 Conference.

Luis Torgo (2018). Data Mining with R: Learning with Case Studies, Second Edition (chinese edition). China Machine Press (CMP).

Luís Torgo, Stan Matwin, Gary Weiss, Nuno Moniz, Paula Branco (2018). Cost-Sensitive Learning: Preface. Proceedings of Machine Learning Research (PMLR).

Vitor Cerqueira, Fabio Pinto, Luis Torgo, Carlos Soares, Nuno Moniz (2018). Constructive Aggregation and its Application to Forecasting with Dynamic Ensembles. Proceedings of the ECML/PKDD’2018 Conference.

Paula Branco, Luís Torgo, Rita P. Ribeiro (2017). SMOGN: a Pre-processing Approach for Imbalanced Regression. Proceedings of Machine Learning Research (PMLR).

Nuno Moniz, Paula Branco, Luis Torgo (2017). Resampling Strategies for Imbalanced Time Series Forecasting. International Journal of Data Science and Analytics.

Paula Branco, Luis Torgo, Rita P. Ribeiro (2017). Relevance-based Evaluation Metrics for Multi-class Imbalanced Domains. Advances in Knowledge Discovery and Data Mining - 21th Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings.

Luís Torgo, Bartoz Krawczyk, Paula Branco, Nuno Moniz (2017). Learning with Imbalanced Domains: preface. Proceedings of Machine Learning Research (PMLR).

Paula Branco, Luis Torgo, Rita P. Ribeiro, Eibe Frank, Bernhard Pfahringer, Markus Michael Rau (2017). Learning Through Utility Optimization in Regression Tasks. IEEE International Conference on Data Science and Advanced Analytics (DSAA’2017).

Paula Branco, Luis Torgo, Rita P. Ribeiro (2017). Exploring Resampling with Neighborhood Bias on Imbalanced Regression Problems. Proceedings of 18th EPIA Conference on Artificial Intelligence (EPIA 2017).

Nuno Moniz, Paula Branco, Luís Torgo (2017). Evaluation of Ensemble Methods in Imbalanced Regression Tasks. Proceedings of Machine Learning Research (PMLR).

M. Monteiro, J. Séneca, Luis Torgo, D. F. R. Cleary, N. C. M. Gomes, A. E. Santoro, C. Magalhães (2017). Environmental controls on estuarine nitrifying communities along a salinity gradient. Aquatic Microbial Ecology.

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Vitor Cerqueira, Luis Torgo, Mariana Oliveira, Bernhard Pfahringer (2017). Dynamic and Heterogeneous Ensembles for Time Series Forecasting. IEEE International Conference on Data Science and Advanced Analytics (DSAA’2017).

Luís Torgo (2017). Data Mining with R: Learning with Case Studies, Second Edition. Chapman and Hall/CRC.

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Vítor Cerqueira, Luís Torgo, Fábio Pinto, Carlos Soares (2017). Arbitrated Ensemble for Time Series Forecasting. Proceedings of the ECML/PKDD’2017 Conference.

Vitor Cerqueira, Luis Torgo, Carlos Soares (2017). Arbitrated Ensemble for Solar Radiation Forecasting. Proceedings of IWANN’2017.

Nuno Moniz, Luís Torgo, Magdalini Eirinaki, Paula Branco (2017). A Framework for Recommendation of Highly Popular News Lacking Social Feedback. New Generation Computing.

Vitor Cerqueira, Luis Torgo, Jasmina Smailović, Igor Mozetic (2017). A Comparative Study of Performance Estimation Methods for Time Series Forecasting. IEEE International Conference on Data Science and Advanced Analytics (DSAA’2017).

M Monteiro, J Séneca, L Torgo, Batista M, C Lee, C Cary, C Magalhães (2016). The impact of environmental changes on nitrifyng communities from the Dry Valleys of Antarctica. Proceedings of XXXIV SCAR.

Nuno Moniz, Paula Branco, Luis Torgo (2016). Resampling Strategies for Imbalanced Time Series. Proceedings of DSAA 2016.

Luís Torgo (2016). Regression Trees. In: Encyclopedia of Machine Learning and Data Mining.

C. Bartilotti, A. Santos, R. Marques, A. Silva, C. Churro, C. Sónia, H. Ribeiro, AP. Mucha, F. Carvalho, CMR. Almeida, I. Azevedo, S. Ramos, T. Borges, S. Leandro, A. Dias, E. Silva, H. Ferreira, I. Dias, JM. Almeida, L. Torgo, N. Dias, P. Jorge, A. Martins (2016). Presenting the MarinEye project – Development and validation of a prototype for multitrophic oceanic monitoring. Proceedings of ASC 2016- ICES Anual Science Meeting.

Mariana Oliveira, Luis Torgo, Vítor Santos Costa (2016). Predicting Wildfires: Propositional and Relational Spatio-Temporal Pre-Processing Approaches. Proceedings of Discovery Science 2016.

Luís Torgo (2016). Model Trees. In: Encyclopedia of Machine Learning and Data Mining.

C Magalhães, C Lee, M Monteiro, L Torgo, C. Cary (2016). Everything is not everywhere: Antarctica Dry Valleys as an extreme counter example. Proceedings of XXXIV SCAR.

J Séneca, C Magalhães, M Monteiro, L Torgo, C Lee, C Cary (2016). Distribution of prokaryotic communities and NifH gene diversity in the extrem Darwin Mountains, Abtarctica. Proceedings of XXXIV SCAR.

C. Magalhães, J. Séneca, C. Leite, M. Monteiro, C. Bartilotti, A. Santos, T. Kahlke, J. Tolman, R. Pires, R. Costa, L. Torgo (2016). Distribution and Environmental Controls on Marine Nitrogen Biogeochemical Functions. Proceedings of 41st CIESM Congress.

C. Magalhães, AP. Mucha, F. Carvalho, H. Ribeiro, CNR. Almeida, I. Azevedo, S. Ramos, T. Borges, S. Leandro, A. Santos, A. Silva, C. Bartilotti, S. Cotrim, R. Marques, C. Churro, A. Dias, H. Ferreira, I. Dias, JM. Almeida, L. Torgo, M. Oliveira, N. Dias, P. Jorge, A. Martins, E. Silva (2016). Development of an autonomous system for integrated marine monitoring. Proceedings of XIX Iberian Symposium on Marine Biology Studies.

C Magalhães, AP Mucha, F Carvalho, H Ribeiro, CNR Almeida, I Azevedo, S Ramos, T Borges, S Leandro, A Santos, A Silva, C Bartilotti, S Cotrim, R Marques, C Churro, A Dias, H Ferreira, I Dias, JM Almeida, L Torgo, M Oliveira, N Dias, P Jorge, A Martins, Silva E. (2016). Development of an autonomous system for integrated marine monitoring. Proceedings of 41st CIESM Congress.

Paula Branco, Rita Ribeiro, Luis Torgo (2016). A UBL: an R package for Utility-based Learning. CoRR.

paulaPD, Luis Torgo, rita (2016). A Survey of Predictive Modeling on Imbalanced Domains. ACM Comput. Surv..

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Luis Torgo, Paula Branco, Rita P. Ribeiro, Bernhard Pfahringer (2015). Re-sampling Strategies for Regression. Expert Systems.

Paula Branco, Luis Torgo, Rita Ribeiro (2015). A Survey of Predictive Modelling under Imbalanced Distributions. CoRR.

Mariana Oliveira, Luis Torgo (2014). Ensembles for Time Series Forecasting. Proceedings of Asian Conference on Machine Learning (ACML’2014)..

Luis Torgo (2014). An Infra-Structure for Performance Estimation and Experimental Comparison of Predictive Models in R. CoRR.

Luís Torgo, Rita P. Ribeiro, Bernhard Pfahringer, Paula Branco (2013). SMOTE for Regression. Proceedings of EPIA’2013.

Joaquin Vanschoren, Jan N. van Rijn, Bernd Bischl, Luis Torgo (2013). OpenML: networked science in machine learning. SIGKDD Explorations Newsletter.

J. van Rijn, B. Bischl, Luís Torgo, B. Gao (2013). OpenML: A collaborative Science Platform. Proceedings of ECML/PKDD’2013.

Jan N van Rijn, Venkatesh Umaashankar, Simon Fischer, Bernd Bischl, Luis Torgo, Bo Gao, Patrick Winter, Bernd Wiswedel, Michael R Berthold, Joaquin Vanschoren (2013). A RapidMiner extension for Open Machine Learning. RapidMiner Community Meeting and Conference, 2013.

Orlando Ohashi, Luís Torgo (2012). Wind speed forecasting using spatio-temporal indicators. ECAI 2012 - 20th European Conference on Artificial Intelligence.

O. Ohashi, L. Torgo (2012). Spatial Interpolation Using Multiple Regression. Data Mining (ICDM), 2012 IEEE 12th International Conference on.

Luís Torgo (2012). Data Mining with R: Learning with Case Studies (Chinese Edition). China Machine Press.

Luís Torgo (2011). Regression Trees. In: Encyclopedia of Machine Learning.

Luís Torgo (2011). Model Trees. In: Encyclopedia of Machine Learning.

Luís Torgo, Orlando Ohashi (2011). 2D-interval predictions for time series. Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD’2011.

Luís Torgo, Carlos Soares (2010). Resource-bounded Outlier Detection Using Clustering Methods. In: Data Mining for Business Applications.

Manuel Herrera, Lu\‘is Torgo, Joaquin Izquierdo, Rafael Perez-Garcia (2010). Predictive models for forecasting hourly urban water demand. Journal of Hydrology.

Lu\‘is Torgo, Rita P. Ribeiro (2010). Modelos de Previs\~ao de Valores Extremos e Raros. Boletim da Sociedade Portuguesa de Estat{‘i}stica.

Orlando Ohashi, Luís Torgo, Rita P. Ribeiro (2010). Interval Forecast of Water Quality Parameters. ECAI 2010 - 19th European Conference on Artificial Intelligence.

Luís Torgo (2010). Data Mining with R: Learning with Case Studies. CRC Press.

Luís Torgo, Rita P. Ribeiro (2009). Precision and Recall for Regression.. Discovery Science.

Rita Ribeiro, Luís Torgo (2008). 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).

Rita Ribeiro, Luis Torgo (2008). A Comparative Study on Predicting Algae Blooms in Douro River, Portugal. Ecological Modelling - Selected Papers from the 5th European Conference on Ecological Modelling.

Luís Torgo, Rita Ribeiro (2007). Utility-based Regression. Proceedings of the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD 2007).

R. Ribeiro, L. Torgo (2006). Rule-based Prediction of Rare Extreme Values. Proceedings of the 9th International Conference on Discovery Science (DS’2006).

L. Torgo, R. Ribeiro (2006). Predicting Rare Extreme Values. Proceedings of the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’2006).

L. Torgo (2005). Regression Error Characteristic Surfaces. Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2005).

J. Gama, R. Camacho, P. Brazdil, A. Jorge, L. Torgo (2005). Machine Learning: ECML 2005: 16th European Conference on Machine Learning. Springer.

A. Jorge, L. Torgo, P. Brazdil, R. Camacho, J. Gama (2005). Knowledge Discovery in Databases: PKDD 2005: 9th European Conference on Principles and Practice of Knowledge Discovery in Databases. Springer.

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

A. Loureiro, L. Torgo, C. Soares (2004). Outlier Detection using Clustering Methods: a data cleaning application. Proceedings of KDNet Symposium on Knowledge-based Systems for the Public Sector.

L. Torgo, R. Ribeiro (2003). Predicting Outliers. Proceedings of Principles of Data Mining and Knowledge Discovery (PKDD’03).

Rita P. Ribeiro, Luís Torgo (2003). Predicting Harmful Algae Blooms.. EPIA.

L. Torgo, J. P. Costa (2003). Clustered Partial Linear Regression. Machine Learning.

L. Torgo (2002). Computationally Efficient Linear Regression Trees. Classification, Clustering and Data Analysis: recent advances and applications (Proc. of IFCS 2002).

L. Torgo (2001). A study on end-cut preference in least squares regression trees. Proceedings of the Portuguese AI Conference (EPIA 2001).

Lu\‘is Torgo (2000). Thesis: Inductive learning to tree-based regression models.. AI Commun..

L. Torgo (2000). Partial Linear Trees. Proceedings of the 17th International Conference on Machine Learning (ICML 2000).

L. Torgo (2000). Efficient and Comprehensible Local Regression. Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2000).

L. Torgo, J. P. Costa (2000). Clustered Partial Linear Regression. Proceedings of the 11th European Conference on Machine Learning (ECML 2000).

L. Torgo, J. P. Costa (2000). Clustered Partial Linear Regression. Proceedings of the Fifth International Workshop on Multistrategy Learning (MSL-2000).

L. Torgo, J. P. Costa (2000). Clustered Multivariate Regression. Data Analysis, Classification, and Related Methods.

L. Torgo (1999). Predicting the Density of Algae Communities using Local Regression Trees. Proceedings of the European Congress on Intelligent Techniques and Soft Computing (EUFIT’99).

L. Torgo (1999). Inductive Learning of Tree-based Regression Models. Faculty of Sciences, University of Porto.

L. Torgo (1998). Error Estimates for Pruning Regression Trees. Proceedings of the 10th European Conference on Machine Learning.

L. Torgo (1998). A Comparative Study of Reliable Error Estimators for Pruning Regression Trees. Proceedings of the Iberoamericam Conference on AI (IBERAMIA-98).

L. Torgo (1997). Kernel Regression Trees. Poster papers of the European Conference on Machine Learning (ECML-97).

L. Torgo (1997). Functional Models for Regression Tree Leaves. Proceedings of the 14th International Conference on Machine Learning.

Luís Torgo (1995). Data Fitting with Rule-based Regression. Proceedings of the 2nd International Workshop on Artificial Intelligence Techniques (AIT 1995).

Luís Torgo (1995). Applying Propositional Learning to Time Series Prediction. Workshop on Statistics, Machine Learning and Knowledge Discovery in Databases.