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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Chemosphere, pp. Dealing with Insufficient Data. He has a strong experience of teaching different subjects at different academic levels but also in non-academic settings.

Adapting Peepholing ,uis Regression Trees.

Most of the main data mining processes and techniques are covered in the book by means of the presentation of four detailed case studies: Interval Forecast of Water Quality Parameters. Resampling with Neighbourhood Bias on Imbalanced Domains. Functional Models for Regression Tree Leaves. I puis to see my research being applied and thus I try to maintain a network of collaborations with researchers from other areas.


Online Observatory Tools for detecting frauds on online digital advertisment. University of Porto, Portugal. Meta Learning for Utility Maximization in Regression.

Selected Publications

Data Mining Machine Learning. Staying Zombies or Awaiting for Resurrection? Arbitrated Ensemble for Time Series Forecasting. Detecting Errors in Foreign Trade Transactions: A comparative study of approaches to forecast the correct trading actions.

Two physicochemically diverse sediment samples from the Lima Estuary Portugal were spiked individually with 25 mg L-1 of each PAH in laboratory designed microcosms.

We created sentiment models and out-of-sample datasets, which are used as a gold standard for evaluations. DeepSense A solution for data analytics in the ocean economy.

Luis Torgo

Brazilian symposium on artificial intelligence, Design of an end-to-end method to extract information from tables. Ensembles for Time Series Forecasting. Lis Systems 32 3: Regression error characteristic surfaces. Global Trendings and Next Challenges.

Verified email at dal. With an extensive set of experiments, we provide evidence of the advantage of introducing a neighbourhood bias ulis the resampling strategies for both classification and regression tasks with imbalanced data sets. Expert Systems 35 4 Nuno Moniz, Todgo Torgo. He has been involved in many research projects under different roles and involving different types of organizations.


Data Mining with R: Paula BrancoRita P. New articles related to this author’s research. Naphthalene and fluoranthene levels decreased over time with distinct degradation dynamics varying with sediment type.

Book entered the production stage. Resampling Strategies for Imbalanced Time Series. Aquatic Microbial Ecology80 2pp.

Dr. Luis Torgo – Faculty of Computer Science – Dalhousie University

Email address for updates. Rule Combination in Inductive Learning.

Co-authors View all Rita P. Tofgo Imbalanced domains are an important problem that arises in predictive tasks causing a loss in the performance on the most relevant cases for the user. Evaluation procedures for forecasting with spatio-temporal data.