Luı́s Torgo
- Artificial Intelligence top 0.5%
- Imbalanced Data Classification Techniques 20
- Machine Learning and Data Classification 12
- Anomaly Detection Techniques and Applications 9
- Signal Processing top 2%
- Time Series Analysis and Forecasting 17
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- Forecasting Techniques and Applications 14
- Stock Market Forecasting Methods 11
- Environmental Engineering top 5%
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- Data Mining Algorithms and Applications 11
- Spam and Phishing Detection 9
- Co-authors
- Paula BrancoRita P. RibeiroBernd BischlJoaquin VanschorenJan N. van RijnVítor CerqueiraManuel HerreraRafael Pérez-García
- Journals
- Machine Learning (6 papers)Frontiers in Microbiology (1 paper)Cold Spring Harbor Symposia on Quantitative Biology (1 paper)
- Partner nations
- PortugalCanadaNew Zealand
In The Last Decade
Luı́s Torgo
97 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 190
- Artificial Intelligence 1.7k
- Signal Processing 272
- Management Science and Operations Research 304
- Health Information Management 104
- Environmental Engineering 303
Countries citing papers authored by Luı́s Torgo
This map shows the geographic impact of Luı́s Torgo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Luı́s Torgo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luı́s Torgo more than expected).
Fields of papers citing papers by Luı́s Torgo
This network shows the impact of papers produced by Luı́s Torgo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Luı́s Torgo. The network helps show where Luı́s Torgo may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Luı́s Torgo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 2 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 15 | |
| 4 | 2024 | 2 | |
| 5 | 2020 | 181 | |
| 6 | A Brief Overview on the Strategies to Fight Back the Spread of False Information | 2019 | 1 |
| 7 | 2nd Workshop on Learning with Imbalanced Domains: Preface | 2018 | 1 |
| 8 | REBAGG: REsampled BAGGing for Imbalanced Regression | 2018 | 11 |
| 9 | Evaluation of Ensemble Methods in Imbalanced Regression Tasks | 2017 | 10 |
| 10 | SMOGN: a Pre-processing Approach for Imbalanced Regression | 2017 | 90 |
| 11 | Ensembles for Time Series Forecasting | 2014 | 31 |
| 12 | Classifying News Stories with a Constrained Learning Strategy to Estimate the Direction of a Market Index. | 2012 | 8 |
| 13 | 2011 | 10 | |
| 14 | Classifying news stories to estimate the direction of a stock market index | 2011 | 9 |
| 15 | A Contextual Classification Strategy for Polarity Analysis of Direct Quotations from Financial News | 2011 | 4 |
| 16 | Machine Learning: ECML 2005: 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings (Lecture Notes in Computer Science ... / Lecture Notes in Artificial Intelligence) | 2005 | 1 |
| 17 | Inductive learning of tree-based regression models[1]Available at http:www.ncc.up.pt/ | 2000 | 9 |
| 18 | Partial Linear Trees | 2000 | 7 |
| 19 | Data Fitting with Rule-Based Regression | 1995 | 3 |
| 20 | Applying Propositional Learning to Time Series Prediction | 1995 | 1 |
About Luı́s Torgo
Luı́s Torgo is a scholar working on Signal Processing, Management Science and Operations Research, Artificial Intelligence, Information Systems and Health Information Management, having authored 102 papers that have together received 3.7k indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (20 papers), Time Series Analysis and Forecasting (17 papers), Forecasting Techniques and Applications (14 papers), Machine Learning and Data Classification (12 papers), Data Mining Algorithms and Applications (11 papers), Stock Market Forecasting Methods (11 papers), Spam and Phishing Detection (9 papers) and Anomaly Detection Techniques and Applications (9 papers). The work is most often cited by research in Artificial Intelligence (1.7k citations), Signal Processing (272 citations), Management Science and Operations Research (304 citations), Health Information Management (104 citations) and Environmental Engineering (303 citations). Luı́s Torgo has collaborated with scholars based in Portugal, Canada and New Zealand. Frequent co-authors include Paula Branco, Rita P. Ribeiro, Bernd Bischl, Joaquin Vanschoren, Jan N. van Rijn, Vítor Cerqueira, Manuel Herrera, Rafael Pérez-García, Joaquín Izquierdo and Igor Mozetič. Their work appears in journals such as Machine Learning, Frontiers in Microbiology, Cold Spring Harbor Symposia on Quantitative Biology, International Journal of Forecasting and International Journal on Document Analysis and Recognition (IJDAR).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.