LUIS TORGO PDF

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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Walter Van de Velde. Meta Learning for Utility Maximization in Regression. Book went to the printer! Nitrolimit Life at the Edge: This paper focuses on imbalanced domains in both classification and regression tasks.

Luís Torgo – personal home page

Learning with Imbalanced Domains: Predicting Harmful Algae Blooms. Data Mining I CC He has been doing research in the area of Data Mining and Machine Learning sinceand has published over papers in torbo foruns of these areas. Utility-based Regression Ensembles for Time Series Forecasting.

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.

kuis I love to see my research being applied and thus I try to maintain a network of collaborations with researchers from other areas. Remove your e-mail address form our mailing list. PMLR88, pp.

Proceedings of Discovery Science Current Trends in Knowledge Acquisition, Evaluation procedures for forecasting with spatio-temporal data. Co-authors View all Rita P. The results of this study contribute to the understanding of the dissimilatory nitrate-reducing pathways and help uncover their involvement tprgo degradation of PAHs, which lyis be crucial for directing remediation strategies of PAH-contaminated anoxic sediments.

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He has a strong experience of teaching different subjects at different academic levels but also in non-academic settings.

Selected Publications

Dealing with Insufficient Data. Online Observatory Tools for detecting frauds on online digital advertisment. Precision and Recall for Regression. Socially Driven News Recommendation. Arbitrated Ensemble for Solar Luid Forecasting. Resampling with Neighbourhood Bias on Imbalanced Domains. We find no significant difference between the best cross-validation and sequential validation. Adapting Peepholing to Regression Trees. 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.

Power and Energy Systems. Wind speed forecasting using spatio-temporal indicators. Nuno Moniz, Luis Torgo. This book is about learning how to use R for lluis data mining. R academic applied-research basic-research biology concluded consulting-projects cost-sensitive learning costs ensembles evaluation feature engineering imbalance distributions imbalanced distributions imbalanced domains metal learning ongoing ongoing-projects past-projects phd postdoc regression trees relational learning spatiotemporal text mining time series utility utility’based learning.

New articles by this author.

Joaquim Pinto da Costa. Clustered Partial Linear Regression. By tkrgo this form, you give permission to the use of your personal data according to the conditions above. This is accomplished luiz presenting a series of illustrative case studies for which all necessary steps, code and data are provided to the reader.

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How to evaluate torrgo classifiers for Twitter time-ordered data? View all Supervised Theses. Functional Models for Regression Tree Leaves. Resampling Strategies for Imbalanced Time Series.

Terms of Use Privacy Policy Imprint. Environmental controls on estuarine nitrifying communities along a salinity gradient. If you need to update your contact information or clarify any questions related to the newsletter, please send an email to scom inesctec. Resampling strategies for imbalanced time series forecasting. Expert Systems 35 4 Data tlrgo with R: Abstract 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.

Predictive Analytics and the Ocean Abstract Social media are becoming an increasingly important source of information about the public mood regarding issues such as elections, Brexit, stock market, etc.

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