Luís Torgo

Orcid: 0000-0002-6892-8871

Affiliations:
  • University of Porto, Portugal


According to our database1, Luís Torgo authored at least 120 papers between 1991 and 2023.

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Bibliography

2023
Model Selection for Time Series Forecasting An Empirical Analysis of Multiple Estimators.
Neural Process. Lett., December, 2023

Early anomaly detection in time series: a hierarchical approach for predicting critical health episodes.
Mach. Learn., November, 2023

STUDD: a student-teacher method for unsupervised concept drift detection.
Mach. Learn., November, 2023

Automated imbalanced classification via layered learning.
Mach. Learn., June, 2023

Subgroup mining for performance analysis of regression models.
Expert Syst. J. Knowl. Eng., 2023

Multi-output Ensembles for Multi-step Forecasting.
CoRR, 2023

2022
A Survey on Spatio-temporal Data Analytics Systems.
ACM Comput. Surv., January, 2022

A case study comparing machine learning with statistical methods for time series forecasting: size matters.
J. Intell. Inf. Syst., 2022

Exceedance Probability Forecasting via Regression for Significant Wave Height Forecasting.
CoRR, 2022

4th Workshop on Learning with Imbalanced Domains: Preface.
Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2022

A Clustering-based Approach for Predicting the Future Location of a Vessel.
Proceedings of the 35th Canadian Conference on Artificial Intelligence, Toronto, Ontario, 2022

2021
Towards a pragmatic detection of unreliable accounts on social networks.
Online Soc. Networks Media, 2021

Biased resampling strategies for imbalanced spatio-temporal forecasting.
Int. J. Data Sci. Anal., 2021

SWS: an unsupervised trajectory segmentation algorithm based on change detection with interpolation kernels.
GeoInformatica, 2021

Beyond Average Performance - exploring regions of deviating performance for black box classification models.
CoRR, 2021

Model Compression for Dynamic Forecast Combination.
CoRR, 2021

Model Selection for Time Series Forecasting: Empirical Analysis of Different Estimators.
CoRR, 2021

An organized review of key factors for fake news detection.
CoRR, 2021

3rd Workshop on Learning with Imbalanced Domains: Preface.
Proceedings of the Third International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2021

Active Learning for Imbalanced Domains: the ALOD and ALOD-RE Algorithms.
Proceedings of the 8th IEEE International Conference on Data Science and Advanced Analytics, 2021

2020
Evaluating time series forecasting models: an empirical study on performance estimation methods.
Mach. Learn., 2020

Visual interpretation of regression error.
Expert Syst. J. Knowl. Eng., 2020

Knowledge-based Reliability Metrics for Social Media Accounts.
Proceedings of the 16th International Conference on Web Information Systems and Technologies, 2020

Wise Sliding Window Segmentation: A Classification-Aided Approach for Trajectory Segmentation.
Proceedings of the Advances in Artificial Intelligence, 2020

2019
A review on web content popularity prediction: Issues and open challenges.
Online Soc. Networks Media, 2019

Arbitrage of forecasting experts.
Mach. Learn., 2019

A Brief Overview on the Strategiesto Fight Back the Spreadof False Information.
J. Web Eng., 2019

Pre-processing approaches for imbalanced distributions in regression.
Neurocomputing, 2019

Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters.
CoRR, 2019

On Feature Selection and Evaluation of Transportation Mode Prediction Strategies.
Proceedings of the Workshops of the EDBT/ICDT 2019 Joint Conference, 2019

A Study on the Impact of Data Characteristics in Imbalanced Regression Tasks.
Proceedings of the 2019 IEEE International Conference on Data Science and Advanced Analytics, 2019

Explaining the Performance of Black Box Regression Models.
Proceedings of the 2019 IEEE International Conference on Data Science and Advanced Analytics, 2019

Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes.
Proceedings of the Discovery Science - 22nd International Conference, 2019

The CURE for Class Imbalance.
Proceedings of the Discovery Science - 22nd International Conference, 2019

2018
News Popularity in Multiple Social Media Platforms.
Dataset, February, 2018

Twitter as a Source for Time- and Domain-Dependent Sentiment Lexicons.
Proceedings of the Social Network Based Big Data Analysis and Applications, 2018

Resampling with neighbourhood bias on imbalanced domains.
Expert Syst. J. Knowl. Eng., 2018

How to evaluate sentiment classifiers for Twitter time-ordered data?
CoRR, 2018

Multi-Source Social Feedback of Online News Feeds.
CoRR, 2018

Current State of the Art to Detect Fake News in Social Media: Global Trendings and Next Challenges.
Proceedings of the 14th International Conference on Web Information Systems and Technologies, 2018

Cost-Sensitive Learning: Preface.
Proceedings of the International Workshop on Cost-Sensitive Learning, 2018

2nd Workshop on Learning with Imbalanced Domains: Preface.
Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2018

Constructive Aggregation and Its Application to Forecasting with Dynamic Ensembles.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

REBAGG: REsampled BAGGing for Imbalanced Regression.
Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2018

Evaluation Procedures for Forecasting with Spatio-Temporal Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Analysis and Detection of Unreliable Users in Twitter: Two Case Studies.
Proceedings of the Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2018

Contributions to the Detection of Unreliable Twitter Accounts through Analysis of Content and Behaviour.
Proceedings of the 10th International Joint Conference on Knowledge Discovery, 2018

The Utility Problem of Web Content Popularity Prediction.
Proceedings of the 29th on Hypertext and Social Media, 2018

MetaUtil: Meta Learning for Utility Maximization in Regression.
Proceedings of the Discovery Science - 21st International Conference, 2018

2017
Regression Trees.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Model Trees.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

A Framework for Recommendation of Highly Popular News Lacking Social Feedback.
New Gener. Comput., 2017

Resampling strategies for imbalanced time series forecasting.
Int. J. Data Sci. Anal., 2017

A comparative study of approaches to forecast the correct trading actions.
Expert Syst. J. Knowl. Eng., 2017

Learning with Imbalanced Domains: Preface.
Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2017

Evaluation of Ensemble Methods in Imbalanced Regression Tasks.
Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2017

Arbitrated Ensemble for Time Series Forecasting.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

SMOGN: a Pre-processing Approach for Imbalanced Regression.
Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2017

Relevance-Based Evaluation Metrics for Multi-class Imbalanced Domains.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017

Arbitrated Ensemble for Solar Radiation Forecasting.
Proceedings of the Advances in Computational Intelligence, 2017

Exploring Resampling with Neighborhood Bias on Imbalanced Regression Problems.
Proceedings of the Progress in Artificial Intelligence, 2017

A Comparative Study of Performance Estimation Methods for Time Series Forecasting.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

Dynamic and Heterogeneous Ensembles for Time Series Forecasting.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

Learning Through Utility Optimization in Regression Tasks.
Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics, 2017

2016
A Survey of Predictive Modeling on Imbalanced Domains.
ACM Comput. Surv., 2016

Data-Driven Relevance Judgments for Ranking Evaluation.
CoRR, 2016

UBL: an R package for Utility-based Learning.
CoRR, 2016

Time-Based Ensembles for Prediction of Rare Events in News Stream.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

Lexicon Expansion System for Domain and Time Oriented Sentiment Analysis.
Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - Volume 1: KDIR, Porto - Portugal, November 9, 2016

Resampling Strategies for Imbalanced Time Series.
Proceedings of the 2016 IEEE International Conference on Data Science and Advanced Analytics, 2016

Predicting Wildfires - Propositional and Relational Spatio-Temporal Pre-processing Approaches.
Proceedings of the Discovery Science - 19th International Conference, 2016

2015
Resampling strategies for regression.
Expert Syst. J. Knowl. Eng., 2015

Socially Driven News Recommendation.
CoRR, 2015

A Survey of Predictive Modelling under Imbalanced Distributions.
CoRR, 2015

Class-Based Outlier Detection: Staying Zombies or Awaiting for Resurrection?
Proceedings of the Advances in Intelligent Data Analysis XIV, 2015

Forecasting the Correct Trading Actions.
Proceedings of the Progress in Artificial Intelligence, 2015

2014
An Infra-Structure for Performance Estimation and Experimental Comparison of Predictive Models in R.
CoRR, 2014

Resampling Approaches to Improve News Importance Prediction.
Proceedings of the Advances in Intelligent Data Analysis XIII, 2014

Ensembles for Time Series Forecasting.
Proceedings of the Sixth Asian Conference on Machine Learning, 2014

2013
OpenML: networked science in machine learning.
SIGKDD Explor., 2013

OpenML: A Collaborative Science Platform.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

SMOTE for Regression.
Proceedings of the Progress in Artificial Intelligence, 2013

2012
Classifying News Stories with a Constrained Learning Strategy to Estimate the Direction of a Market Index.
Int. J. Comput. Sci. Appl., 2012

Spatial Interpolation Using Multiple Regression.
Proceedings of the 12th IEEE International Conference on Data Mining, 2012

Wind speed forecasting using spatio-temporal indicators.
Proceedings of the ECAI 2012, 2012

2011
A Contextual Classification Strategy for Polarity Analysis of Direct Quotations from Financial News.
Proceedings of the Recent Advances in Natural Language Processing, 2011

2D-interval predictions for time series.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Utility-Based Fraud Detection.
Proceedings of the IJCAI 2011, 2011

2010
Resource-bounded Outlier Detection using Clustering Methods.
Proceedings of the Data Mining for Business Applications, 2010

Regression Trees.
Proceedings of the Encyclopedia of Machine Learning, 2010

Model Trees.
Proceedings of the Encyclopedia of Machine Learning, 2010

Interval Forecast of Water Quality Parameters.
Proceedings of the ECAI 2010, 2010

Data Mining with R: Learning with Case Studies
Chapman and Hall/CRC Press, ISBN: 9781439810187, 2010

2009
Detecting Errors in Foreign Trade Transactions: Dealing with Insufficient Data.
Proceedings of the Progress in Artificial Intelligence, 2009

Precision and Recall for Regression.
Proceedings of the Discovery Science, 12th International Conference, 2009

2007
Utility-Based Regression.
Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007

Resource-Bounded Fraud Detection.
Proceedings of the Progress in Artificial Intelligence, 2007

2006
Design of an end-to-end method to extract information from tables.
Int. J. Document Anal. Recognit., 2006

Predicting Rare Extreme Values.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2006

Rule-Based Prediction of Rare Extreme Values.
Proceedings of the Discovery Science, 9th International Conference, 2006

2005
Regression error characteristic surfaces.
Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2005

Adapting Peepholing to Regression Trees.
Proceedings of the Progress in Artificial Intelligence, 2005

2003
Clustered Partial Linear Regression.
Mach. Learn., 2003

Predicting Outliers.
Proceedings of the Knowledge Discovery in Databases: PKDD 2003, 2003

Automatic Selection of Table Areas in Documents for Information Extraction.
Proceedings of the Progress in Artificial Intelligence, 2003

Predicting Harmful Algae Blooms.
Proceedings of the Progress in Artificial Intelligence, 2003

2001
A Study on End-Cut Preference in Least Squares Regression Trees.
Proceedings of the Progress in Artificial Intelligence, 2001

The Use of Domain Knowledge in Feature Construction for Financial Time Series Prediction.
Proceedings of the Progress in Artificial Intelligence, 2001

2000
Thesis: Inductive learning to tree-based regression models.
AI Commun., 2000

Efficient and Comprehensible Local Regression.
Proceedings of the Knowledge Discovery and Data Mining, 2000

Partial Linear Trees.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

1998
Dynamic Discretization of Continuous Attributes.
Proceedings of the Progress in Artificial Intelligence, 1998

Error Estimators for Pruning Regression Trees.
Proceedings of the Machine Learning: ECML-98, 1998

1997
Regression Using Classification Algorithms.
Intell. Data Anal., 1997

Functional Models for Regression Tree Leaves.
Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

Search-Based Class Discretization.
Proceedings of the Machine Learning: ECML-97, 1997

1996
Regression by Classification.
Proceedings of the Advances in Artificial Intelligence, 1996

1993
Rule Combination in Inductive Learning.
Proceedings of the Machine Learning: ECML-93, 1993

Controlled Redundancy in Incremental Rule Learning.
Proceedings of the Machine Learning: ECML-93, 1993

1991
Panel: Learning in Distributed Systems and Multi-Agent Environments.
Proceedings of the Machine Learning, 1991


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