Proceedings of KDNet Symposium on Knowledge-based systems for the Public Sector, , Functional models for regression tree leaves. L Torgo. List of computer science publications by Luís Torgo. Luis Torgo is an Associate Professor of the Department of Computer Science of the Faculty of Sciences of the University of Porto, Portugal. He is a senior.

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The problem we address concerns the procedures used to obtain reliable estimates torgoo performance measures, and whether the temporal ordering of the training and test data matters.

Controlled Redundancy in Incremental Rule Learning. Their combined citations are counted only for the first article. Proceedings of Discovery Science Aquatic Microbial Ecology80 2pp.

Selected Publications

Regression error characteristic surfaces. Nuno Moniz, Luis Torgo. Regression by classification L Torgo, J Gama Brazilian symposium on artificial intelligence, Chinese edition of the book torgk out! Verified email at dal. The system can’t perform the operation now.

Global Trendings and Next Challenges. Data Mining I CC Co-authors View all Rita P. Please check the confirmation e-mail of your application to obtain the access code. Clustered Partial Linear Regression. Two physicochemically diverse sediment samples liis the Lima Estuary Portugal were spiked individually with 25 mg L-1 of each PAH in laboratory designed microcosms.


Recent Publications More Publications. The book writing style establishes it as a good source for practical classes on data mining, but also as an attractive document to professionals working on lyis mining in non-academic environments. Trier 1 Trier 2. Power and Energy Systems.

Expert Systems 35 4 New articles related to this author’s research. Vitor Cerqueira University of Porto Verified email at inesctec. Articles Cited by Co-authors.

Luís Torgo – INESC TEC

Six months in a row as 1 selling Data Mining book at amazon. Dealing with Insufficient Data. Resampling strategies are among the most successful approaches to address imbalanced domains. Spatial Interpolation Using Multiple Regression. Resampling Strategies for Imbalanced Time Series. Expert Systems 34 1 RibeiroBernhard PfahringerPaula Branco: Forecasting the Correct Trading Actions. International Journal of Data Science and Analytics33, pp. Luis Torgo main contributions to the state of the art on data mining and machine learning are related with tree-based regression methods and more recently with utility-based forecasting methods.

His current broad research interests revolve around analyzing data from dynamic environments, with a particular focus on time and space-time dependent data sets, in the search for unexpected events. Potential of dissimilatory nitrate reduction pathways in polycyclic aromatic hydrocarbon degradation. Terms of Use Privacy Policy Imprint.


European Conference on Machine Learning, Predictive Analytics and the Ocean Predicting Harmful Algae Blooms.

Portuguese conference on artificial intelligence, The following articles are merged in Torrgo. New citations to this author. Applications to Financial Trading. In that case, your data will be automatically deleted from our information system. However, we observe that all cross-validation variants tend to torgi the performance, while the sequential methods tend to underestimate it.

Data Mining with R. With an extensive set of experiments, we provide evidence of the advantage of introducing a neighbourhood bias in the resampling strategies for both classification and regression tasks with imbalanced data sets.

Manuel Herrera University of Cambridge Verified email at cam.

Arbitrated Ensemble for Time Series Forecasting. Naphthalene and fluoranthene levels decreased over time with distinct degradation dynamics varying with sediment type.