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ORCIDLuís Torgo
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- affiliation: University of Porto, Portugal
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2020 – today
- 2024
[c74]Luis Roque
, Carlos Soares, Luís Torgo:
RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms. KDD 2024: 2491-2499- [i22]Luis Roque, Carlos Soares, Luís Torgo:
RHiOTS: A Framework for Evaluating Hierarchical Time Series Forecasting Algorithms. CoRR abs/2408.03399 (2024) - 2023
- [j28]João Pimentel, Paulo J. Azevedo, Luís Torgo:
Subgroup mining for performance analysis of regression models. Expert Syst. J. Knowl. Eng. 40(1) (2023) - [j27]Vítor Cerqueira, Luís Torgo, Paula Branco, Colin Bellinger:
Automated imbalanced classification via layered learning. Mach. Learn. 112(6): 2083-2104 (2023) - [j26]Vítor Cerqueira, Heitor Murilo Gomes, Albert Bifet, Luís Torgo:
STUDD: a student-teacher method for unsupervised concept drift detection. Mach. Learn. 112(11): 4351-4378 (2023) - [j25]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Early anomaly detection in time series: a hierarchical approach for predicting critical health episodes. Mach. Learn. 112(11): 4409-4430 (2023) - [j24]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Model Selection for Time Series Forecasting An Empirical Analysis of Multiple Estimators. Neural Process. Lett. 55(7): 10073-10091 (2023) - [e6]Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michal Wozniak, Shuo Wang:
Fifth International Workshop on Learning with Imbalanced Domains: Theory and Applications, 18 September 2023, LIDTA@ECML-PKDD, Turin, Italy. Proceedings of Machine Learning Research 241, PMLR 2023 [contents] - [i21]Vítor Cerqueira, Luís Torgo:
Multi-output Ensembles for Multi-step Forecasting. CoRR abs/2306.14563 (2023) - 2022
- [j23]Md. Mahbub Alam, Luís Torgo, Albert Bifet:
A Survey on Spatio-temporal Data Analytics Systems. ACM Comput. Surv. 54(10s): 219:1-219:38 (2022) - [j22]Vítor Cerqueira, Luís Torgo, Carlos Soares:
A case study comparing machine learning with statistical methods for time series forecasting: size matters. J. Intell. Inf. Syst. 59(2): 415-433 (2022) - [c73]Md. Mahbub Alam, Luís Torgo:
A Clustering-based Approach for Predicting the Future Location of a Vessel. Canadian AI 2022 - [c72]Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michal Wozniak, Shuo Wang:
4th Workshop on Learning with Imbalanced Domains: Preface. LIDTA 2022: 1-7 - [e5]Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michal Wozniak, Shuo Wang:
Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, LIDTA 2022, Grenoble, France, September 23, 2022. Proceedings of Machine Learning Research 183, PMLR 2022 [contents] - [i20]Vítor Cerqueira, Luís Torgo, Paula Branco, Colin Bellinger:
Automated Imbalanced Classification via Layered Learning. CoRR abs/2205.02553 (2022) - [i19]Vítor Cerqueira, Luís Torgo:
Exceedance Probability Forecasting via Regression for Significant Wave Height Forecasting. CoRR abs/2206.09821 (2022) - 2021
- [j21]Mohammad Etemad, Amílcar Soares Júnior, Elham Etemad, Jordan Rose, Luís Torgo, Stan Matwin:
SWS: an unsupervised trajectory segmentation algorithm based on change detection with interpolation kernels. GeoInformatica 25(2): 269-289 (2021) - [j20]Mariana Oliveira, Nuno Moniz, Luís Torgo, Vítor Santos Costa:
Biased resampling strategies for imbalanced spatio-temporal forecasting. Int. J. Data Sci. Anal. 12(3): 205-228 (2021) - [j19]Nuno Guimarães, Álvaro Figueira, Luís Torgo:
Towards a pragmatic detection of unreliable accounts on social networks. Online Soc. Networks Media 24: 100152 (2021) - [c71]Mayukh Bhattacharjee, Hema Sri Kambhampati, Paula Branco, Luís Torgo:
Active Learning for Imbalanced Domains: the ALOD and ALOD-RE Algorithms. DSAA 2021: 1-10 - [c70]Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michal Wozniak, Shuo Wang:
3rd Workshop on Learning with Imbalanced Domains: Preface. LIDTA@ECML/PKDD 2021: 1-6 - [e4]Carlos Soares, Luís Torgo:
Discovery Science - 24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021, Proceedings. Lecture Notes in Computer Science 12986, Springer 2021, ISBN 978-3-030-88941-8 [contents] - [e3]Nuno Moniz, Paula Branco, Luís Torgo, Nathalie Japkowicz, Michal Wozniak, Shuo Wang:
Third International Workshop on Learning with Imbalanced Domains: Theory and Applications, LIDTA 2021, Bilbao, Spain, September 17, 2021. Proceedings of Machine Learning Research 154, PMLR 2021 [contents] - [i18]Nuno Guimarães, Álvaro Figueira, Luís Torgo:
An organized review of key factors for fake news detection. CoRR abs/2102.13433 (2021) - [i17]Vítor Cerqueira, Heitor Murilo Gomes, Albert Bifet, Luís Torgo:
STUDD: A Student-Teacher Method for Unsupervised Concept Drift Detection. CoRR abs/2103.00903 (2021) - [i16]Md. Mahbub Alam, Luís Torgo, Albert Bifet:
A Survey on Spatio-temporal Data Analytics Systems. CoRR abs/2103.09883 (2021) - [i15]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Model Selection for Time Series Forecasting: Empirical Analysis of Different Estimators. CoRR abs/2104.00584 (2021) - [i14]Vítor Cerqueira, Luís Torgo, Carlos Soares, Albert Bifet:
Model Compression for Dynamic Forecast Combination. CoRR abs/2104.01830 (2021) - [i13]Luís Torgo, Paulo Azevedo, Inês Areosa:
Beyond Average Performance - exploring regions of deviating performance for black box classification models. CoRR abs/2109.08216 (2021) - 2020
- [j18]Inês Areosa, Luís Torgo:
Visual interpretation of regression error. Expert Syst. J. Knowl. Eng. 37(6) (2020) - [j17]Vítor Cerqueira, Luís Torgo, Igor Mozetic:
Evaluating time series forecasting models: an empirical study on performance estimation methods. Mach. Learn. 109(11): 1997-2028 (2020) - [c69]Mohammad Etemad, Zahra Etemad, Amílcar Soares Júnior, Vania Bogorny, Stan Matwin, Luís Torgo:
Wise Sliding Window Segmentation: A Classification-Aided Approach for Trajectory Segmentation. Canadian AI 2020: 208-219 - [c68]Nuno Guimarães, Álvaro Figueira, Luís Torgo:
Knowledge-based Reliability Metrics for Social Media Accounts. WEBIST 2020: 339-350 - [i12]Mohammad Etemad, Zahra Etemad, Amílcar Soares Júnior, Vania Bogorny, Stan Matwin, Luís Torgo:
Wise Sliding Window Segmentation: A classification-aided approach for trajectory segmentation. CoRR abs/2003.10248 (2020) - [i11]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health Episodes. CoRR abs/2010.11595 (2020)
2010 – 2019
- 2019
- [j16]Paula Branco, Luís Torgo, Rita P. Ribeiro:
Pre-processing approaches for imbalanced distributions in regression. Neurocomputing 343: 76-99 (2019) - [j15]Álvaro Figueira, Nuno Guimarães, Luís Torgo:
A Brief Overview on the Strategiesto Fight Back the Spreadof False Information. J. Web Eng. 18(4-6): 319-352 (2019) - [j14]Vítor Cerqueira, Luís Torgo, Fábio Pinto, Carlos Soares:
Arbitrage of forecasting experts. Mach. Learn. 108(6): 913-944 (2019) - [j13]Nuno Moniz, Luís Torgo:
A review on web content popularity prediction: Issues and open challenges. Online Soc. Networks Media 12: 1-20 (2019) - [c67]Colin Bellinger, Paula Branco, Luís Torgo:
The CURE for Class Imbalance. DS 2019: 3-17 - [c66]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes. DS 2019: 445-459 - [c65]Mariana Oliveira, Nuno Moniz, Luís Torgo, Vítor Santos Costa:
Biased Resampling Strategies for Imbalanced Spatio-Temporal Forecasting. DSAA 2019: 100-109 - [c64]Inês Areosa, Luís Torgo:
Explaining the Performance of Black Box Regression Models. DSAA 2019: 110-118 - [c63]Paula Branco, Luís Torgo:
A Study on the Impact of Data Characteristics in Imbalanced Regression Tasks. DSAA 2019: 193-202 - [c62]Mohammad Etemad, Amílcar Soares Júnior, Stan Matwin, Luís Torgo:
On Feature Selection and Evaluation of Transportation Mode Prediction Strategies. EDBT/ICDT Workshops 2019 - [c61]Inês Areosa, Luís Torgo:
Visual Interpretation of Regression Error. EPIA (2) 2019: 473-485 - [i10]Vítor Cerqueira, Luís Torgo, Igor Mozetic:
Evaluating time series forecasting models: An empirical study on performance estimation methods. CoRR abs/1905.11744 (2019) - [i9]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters. CoRR abs/1909.13316 (2019) - 2018
- [j12]Paula Branco, Luís Torgo, Rita P. Ribeiro:
Resampling with neighbourhood bias on imbalanced domains. Expert Syst. J. Knowl. Eng. 35(4) (2018) - [c60]Paula Branco, Luís Torgo, Rita P. Ribeiro:
MetaUtil: Meta Learning for Utility Maximization in Regression. DS 2018: 129-143 - [c59]Nuno Moniz, Luís Torgo:
The Utility Problem of Web Content Popularity Prediction. HT 2018: 82-86 - [c58]Nuno Guimarães, Álvaro Figueira, Luís Torgo:
Analysis and Detection of Unreliable Users in Twitter: Two Case Studies. IC3K 2018: 50-73 - [c57]Nuno Guimarães, Álvaro Figueira, Luís Torgo:
Contributions to the Detection of Unreliable Twitter Accounts through Analysis of Content and Behaviour. KDIR 2018: 90-99 - [c56]Luís Torgo, Stan Matwin, Nathalie Japkowicz, Bartosz Krawczyk, Nuno Moniz, Paula Branco:
2nd Workshop on Learning with Imbalanced Domains: Preface. LIDTA@ECML/PKDD 2018: 1-7 - [c55]Paula Branco, Luís Torgo, Rita P. Ribeiro:
REBAGG: REsampled BAGGing for Imbalanced Regression. LIDTA@ECML/PKDD 2018: 67-81 - [c54]Vítor Cerqueira, Fábio Pinto, Luís Torgo, Carlos Soares, Nuno Moniz:
Constructive Aggregation and Its Application to Forecasting with Dynamic Ensembles. ECML/PKDD (1) 2018: 620-636 - [c53]Mariana Oliveira, Luís Torgo, Vítor Santos Costa:
Evaluation Procedures for Forecasting with Spatio-Temporal Data. ECML/PKDD (1) 2018: 703-718 - [c52]Luís Torgo, Stan Matwin, Gary Weiss, Nuno Moniz, Paula Branco:
Cost-Sensitive Learning: Preface. COST@SDM 2018: 1-3 - [c51]Álvaro Figueira, Nuno Guimarães, Luís Torgo:
Current State of the Art to Detect Fake News in Social Media: Global Trendings and Next Challenges. WEBIST 2018: 332-339 - [p2]Nuno Guimarães, Luís Torgo, Álvaro Figueira:
Twitter as a Source for Time- and Domain-Dependent Sentiment Lexicons. Social Network Based Big Data Analysis and Applications 2018: 1-19 - [d1]Luís Torgo, Nuno Moniz:
News Popularity in Multiple Social Media Platforms. UCI Machine Learning Repository, 2018
- [i8]Nuno Moniz, Luís Torgo:
Multi-Source Social Feedback of Online News Feeds. CoRR abs/1801.07055 (2018) - [i7]Igor Mozetic, Luís Torgo, Vítor Cerqueira, Jasmina Smailovic:
How to evaluate sentiment classifiers for Twitter time-ordered data? CoRR abs/1803.05160 (2018) - 2017
- [j11]Luís Baía, Luís Torgo:
A comparative study of approaches to forecast the correct trading actions. Expert Syst. J. Knowl. Eng. 34(1) (2017) - [j10]Nuno Moniz, Paula Branco, Luís Torgo:
Resampling strategies for imbalanced time series forecasting. Int. J. Data Sci. Anal. 3(3): 161-181 (2017) - [j9]Nuno Moniz, Luís Torgo, Magdalini Eirinaki, Paula Branco:
A Framework for Recommendation of Highly Popular News Lacking Social Feedback. New Gener. Comput. 35(4): 417-450 (2017) - [c50]Paula Branco, Luís Torgo, Rita P. Ribeiro, Eibe Frank, Bernhard Pfahringer, Markus Michael Rau:
Learning Through Utility Optimization in Regression Tasks. DSAA 2017: 30-39 - [c49]Vítor Cerqueira, Luís Torgo, Mariana Oliveira, Bernhard Pfahringer:
Dynamic and Heterogeneous Ensembles for Time Series Forecasting. DSAA 2017: 242-251 - [c48]Vítor Cerqueira, Luís Torgo, Jasmina Smailovic, Igor Mozetic:
A Comparative Study of Performance Estimation Methods for Time Series Forecasting. DSAA 2017: 529-538 - [c47]Paula Branco, Luís Torgo, Rita P. Ribeiro:
Exploring Resampling with Neighborhood Bias on Imbalanced Regression Problems. EPIA 2017: 513-524 - [c46]Vítor Cerqueira, Luís Torgo, Carlos Soares:
Arbitrated Ensemble for Solar Radiation Forecasting. IWANN (1) 2017: 720-732 - [c45]Paula Branco, Luís Torgo, Rita P. Ribeiro:
Relevance-Based Evaluation Metrics for Multi-class Imbalanced Domains. PAKDD (1) 2017: 698-710 - [c44]Luís Torgo, Bartosz Krawczyk, Paula Branco, Nuno Moniz:
Learning with Imbalanced Domains: Preface. LIDTA@PKDD/ECML 2017: 1-6 - [c43]Paula Branco, Luís Torgo, Rita P. Ribeiro:
SMOGN: a Pre-processing Approach for Imbalanced Regression. LIDTA@PKDD/ECML 2017: 36-50 - [c42]Nuno Moniz, Paula Branco, Luís Torgo:
Evaluation of Ensemble Methods in Imbalanced Regression Tasks. LIDTA@PKDD/ECML 2017: 129-140 - [c41]Vítor Cerqueira, Luís Torgo, Fábio Pinto, Carlos Soares:
Arbitrated Ensemble for Time Series Forecasting. ECML/PKDD (2) 2017: 478-494 - [r4]Luís Torgo:
Model Trees. Encyclopedia of Machine Learning and Data Mining 2017: 845-848 - [r3]Luís Torgo:
Regression Trees. Encyclopedia of Machine Learning and Data Mining 2017: 1080-1083 - 2016
- [j8]Paula Branco, Luís Torgo, Rita P. Ribeiro:
A Survey of Predictive Modeling on Imbalanced Domains. ACM Comput. Surv. 49(2): 31:1-31:50 (2016) - [c40]Mariana Oliveira, Luís Torgo, Vítor Santos Costa:
Predicting Wildfires - Propositional and Relational Spatio-Temporal Pre-processing Approaches. DS 2016: 183-197 - [c39]Nuno Moniz, Paula Branco, Luís Torgo:
Resampling Strategies for Imbalanced Time Series. DSAA 2016: 282-291 - [c38]Nuno Guimarães, Luís Torgo, Álvaro Figueira:
Lexicon Expansion System for Domain and Time Oriented Sentiment Analysis. KDIR 2016: 463-471 - [c37]Nuno Moniz, Luís Torgo, Magdalini Eirinaki:
Time-Based Ensembles for Prediction of Rare Events in News Stream. ICDM Workshops 2016: 1066-1073 - [i6]Paula Branco, Rita P. Ribeiro, Luís Torgo:
UBL: an R package for Utility-based Learning. CoRR abs/1604.08079 (2016) - [i5]Nuno Moniz, Luís Torgo, João Vinagre:
Data-Driven Relevance Judgments for Ranking Evaluation. CoRR abs/1612.06136 (2016) - 2015
- [j7]Luís Torgo, Paula Branco, Rita P. Ribeiro, Bernhard Pfahringer:
Resampling strategies for regression. Expert Syst. J. Knowl. Eng. 32(3): 465-476 (2015) - [c36]Luís Baía, Luís Torgo:
Forecasting the Correct Trading Actions. EPIA 2015: 560-571 - [c35]Leona Nezvalová, Lubos Popelínský, Luís Torgo, Karel Vaculík:
Class-Based Outlier Detection: Staying Zombies or Awaiting for Resurrection? IDA 2015: 193-204 - [i4]Paula Branco, Luís Torgo, Rita P. Ribeiro:
A Survey of Predictive Modelling under Imbalanced Distributions. CoRR abs/1505.01658 (2015) - [i3]Nuno Moniz, Luís Torgo:
Socially Driven News Recommendation. CoRR abs/1506.01743 (2015) - 2014
- [c34]Mariana Oliveira, Luís Torgo:
Ensembles for Time Series Forecasting. ACML 2014 - [c33]Nuno Moniz, Luís Torgo, Fátima Rodrigues:
Resampling Approaches to Improve News Importance Prediction. IDA 2014: 215-226 - [i2]Joaquin Vanschoren, Jan N. van Rijn, Bernd Bischl, Luís Torgo:
OpenML: networked science in machine learning. CoRR abs/1407.7722 (2014) - [i1]Luís Torgo:
An Infra-Structure for Performance Estimation and Experimental Comparison of Predictive Models in R. CoRR abs/1412.0436 (2014) - 2013
- [j6]Joaquin Vanschoren, Jan N. van Rijn, Bernd Bischl, Luís Torgo:
OpenML: networked science in machine learning. SIGKDD Explor. 15(2): 49-60 (2013) - [c32]Luís Torgo, Rita P. Ribeiro, Bernhard Pfahringer, Paula Branco:
SMOTE for Regression. EPIA 2013: 378-389 - [c31]Jan N. van Rijn, Bernd Bischl, Luís Torgo, Bo Gao, Venkatesh Umaashankar, Simon Fischer, Patrick Winter, Bernd Wiswedel, Michael R. Berthold, Joaquin Vanschoren:
OpenML: A Collaborative Science Platform. ECML/PKDD (3) 2013: 645-649 - 2012
- [j5]Brett Drury, Luís Torgo, José João Almeida:
Classifying News Stories with a Constrained Learning Strategy to Estimate the Direction of a Market Index. Int. J. Comput. Sci. Appl. 9(1): 1-22 (2012) - [c30]Orlando Ohashi, Luís Torgo:
Wind speed forecasting using spatio-temporal indicators. ECAI 2012: 975-980 - [c29]Orlando Ohashi, Luís Torgo:
Spatial Interpolation Using Multiple Regression. ICDM 2012: 1044-1049 - 2011
- [c28]Luís Torgo, Elsa Lopes:
Utility-Based Fraud Detection. IJCAI 2011: 1517-1522 - [c27]Luís Torgo, Orlando Ohashi:
2D-interval predictions for time series. KDD 2011: 787-794 - [c26]Brett Drury, Gaël Dias, Luís Torgo:
A Contextual Classification Strategy for Polarity Analysis of Direct Quotations from Financial News. RANLP 2011: 434-440 - 2010
- [b1]Luís Torgo:
Data Mining with R: Learning with Case Studies. Chapman and Hall/CRC Press 2010, ISBN 9781439810187 - [c25]Orlando Ohashi, Luís Torgo, Rita P. Ribeiro:
Interval Forecast of Water Quality Parameters. ECAI 2010: 283-288 - [p1]Luís Torgo, Carlos Soares:
Resource-bounded Outlier Detection using Clustering Methods. Data Mining for Business Applications 2010: 84-98 - [r2]Luís Torgo:
Model Trees. Encyclopedia of Machine Learning 2010: 684-686 - [r1]Luís Torgo:
Regression Trees. Encyclopedia of Machine Learning 2010: 842-845
2000 – 2009
- 2009
- [c24]Luís Torgo, Rita P. Ribeiro:
Precision and Recall for Regression. Discovery Science 2009: 332-346 - [c23]Luís Torgo, Welma Pereira, Carlos Soares:
Detecting Errors in Foreign Trade Transactions: Dealing with Insufficient Data. EPIA 2009: 435-446 - 2007
- [c22]Luís Torgo:
Resource-Bounded Fraud Detection. EPIA Workshops 2007: 449-460 - [c21]Luís Torgo, Rita P. Ribeiro:
Utility-Based Regression. PKDD 2007: 597-604 - 2006
- [j4]Ana Costa e Silva, Alípio Mário Jorge, Luís Torgo:
Design of an end-to-end method to extract information from tables. Int. J. Document Anal. Recognit. 8(2-3): 144-171 (2006) - [c20]Rita P. Ribeiro, Luís Torgo:
Rule-Based Prediction of Rare Extreme Values. Discovery Science 2006: 219-230 - [c19]Luís Torgo, Rita P. Ribeiro:
Predicting Rare Extreme Values. PAKDD 2006: 816-820 - 2005
- [c18]Luís Torgo, Joana Marques:
Adapting Peepholing to Regression Trees. EPIA 2005: 293-303 - [c17]Luís Torgo:
Regression error characteristic surfaces. KDD 2005: 697-702 - [e2]João Gama, Rui Camacho, Pavel Brazdil, Alípio Jorge, Luís Torgo:
Machine Learning: ECML 2005, 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings. Lecture Notes in Computer Science 3720, Springer 2005, ISBN 3-540-29243-8 [contents] - [e1]Alípio Jorge, Luís Torgo, Pavel Brazdil, Rui Camacho, João Gama:
Knowledge Discovery in Databases: PKDD 2005, 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, October 3-7, 2005, Proceedings. Lecture Notes in Computer Science 3721, Springer 2005, ISBN 3-540-29244-6 [contents] - 2003
- [j3]Luís Torgo, Joaquim Pinto da Costa:
Clustered Partial Linear Regression. Mach. Learn. 50(3): 303-319 (2003) - [c16]Rita P. Ribeiro, Luís Torgo:
Predicting Harmful Algae Blooms. EPIA 2003: 308-312 - [c15]Ana Costa e Silva, Alípio Jorge, Luís Torgo:
Automatic Selection of Table Areas in Documents for Information Extraction. EPIA 2003: 460-465 - [c14]Luís Torgo, Rita P. Ribeiro:
Predicting Outliers. PKDD 2003: 447-458 - 2001
- [c13]Luís Torgo:
A Study on End-Cut Preference in Least Squares Regression Trees. EPIA 2001: 104-115 - [c12]Pedro de Almeida, Luís Torgo:
The Use of Domain Knowledge in Feature Construction for Financial Time Series Prediction. EPIA 2001: 116-129 - 2000
- [j2]Luís Torgo:
Thesis: Inductive learning to tree-based regression models. AI Commun. 13(2): 137-138 (2000) - [c11]Luís Torgo, Joaquim Pinto da Costa:
Clustered Partial Linear Regression. ECML 2000: 426-436 - [c10]Luís Torgo:
Partial Linear Trees. ICML 2000: 1007-1014 - [c9]Luís Torgo:
Efficient and Comprehensible Local Regression. PAKDD 2000: 376-379
1990 – 1999
- 1998
- [c8]Luís Torgo:
Error Estimators for Pruning Regression Trees. ECML 1998: 125-130 - [c7]João Gama, Luís Torgo, Carlos Soares:
Dynamic Discretization of Continuous Attributes. IBERAMIA 1998: 160-169 - 1997
- [j1]Luís Torgo, João Gama:
Regression Using Classification Algorithms. Intell. Data Anal. 1(1-4): 275-292 (1997) - [c6]Luís Torgo, João Gama:
Search-Based Class Discretization. ECML 1997: 266-273 - [c5]Luís Torgo:
Functional Models for Regression Tree Leaves. ICML 1997: 385-393 - 1996
- [c4]Luís Torgo, João Gama:
Regression by Classification. SBIA 1996: 51-60 - 1993
- [c3]Luís Torgo:
Controlled Redundancy in Incremental Rule Learning. ECML 1993: 185-195 - [c2]Luís Torgo:
Rule Combination in Inductive Learning. ECML 1993: 384-389 - 1991
- [c1]Pavel Brazdil, Matjaz Gams, Sati S. Sian, Luís Torgo, Walter Van de Velde:
Panel: Learning in Distributed Systems and Multi-Agent Environments. EWSL 1991: 412-423
Coauthor Index
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