Luís Torgo

发表

Predicting Rare Extreme Values

Luís Torgo, Rita P. Ribeiro, 2006, PAKDD.

Rule Combination in Inductive Learning

Luís Torgo, L. Torgo, 1993, ECML.

Regression Using Classification Algorithms

Luís Torgo, João Gama, João Gama, 1997, Intell. Data Anal..

Socially Driven News Recommendation pdf

Luís Torgo, Nuno Moniz, Nuno Moniz, 2015, ArXiv.

Panel: Learning in Distributed Systems and Multi-Agent Environments

Luís Torgo, Matjaz Gams, Walter Van de Velde, 1991, EWSL.

Resampling with neighbourhood bias on imbalanced domains

Luís Torgo, Rita P. Ribeiro, Paula Branco, 2018, Expert Syst. J. Knowl. Eng..

A Brief Overview on the Strategiesto Fight Back the Spreadof False Information

Luís Torgo, Álvaro Figueira, Nuno Guimarães, 2019, J. Web Eng..

A RapidMiner extension for open machine learning

Luís Torgo, Bernd Bischl, Bo Gao, 2013 .

A Contextual Classification Strategy for Polarity Analysis of Direct Quotations from Financial News

Luís Torgo, Brett Drury, Gaël Dias, 2011, RANLP.

The Utility Problem of Web Content Popularity Prediction

Luís Torgo, Nuno Moniz, L. Torgo, 2018, HT.

Resampling strategies for regression

Luís Torgo, Rita P. Ribeiro, Bernhard Pfahringer, 2015, Expert Syst. J. Knowl. Eng..

Search-Based Class Discretization

Luís Torgo, João Gama, João Gama, 1997, ECML.

Design of an end-to-end method to extract information from tables

Luís Torgo, Alípio Mário Jorge, Ana Costa e Silva, 2006, International Journal of Document Analysis and Recognition (IJDAR).

Utility-Based Fraud Detection

Luís Torgo, Elsa Lopes, L. Torgo, 2011, IJCAI.

A comparative study of approaches to forecast the correct trading actions

Luís Torgo, Luís Baía, L. Torgo, 2017, Expert Syst. J. Knowl. Eng..

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

Luís Torgo, Igor Mozetic, Jasmina Smailovic, 2018, PloS one.

On the Road to Knowledge

Luís Torgo, Dunja Mladenic, Peter A. Flach, 2003 .

APPLYING PROPOSITIONAL LEARNING TO TIME SERIES PREDICTION

Luís Torgo, L. Torgo, 2007 .

Model Trees

Luís Torgo, 2017, Encyclopedia of Machine Learning and Data Mining.

Forecasting the Correct Trading Actions

Luís Torgo, Luís Baía, 2015, EPIA.

Inductive learning of tree-based regression models[1]Available at http:www.ncc.up.pt/

Luís Torgo, 2000 .

ROC Curve

Risto Miikkulainen, Johannes Fürnkranz, Jun Morimoto, 2010, Encyclopedia of Machine Learning.

Market Basket Analysis

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning.

Lexicon Expansion System for Domain and Time Oriented Sentiment Analysis

Luís Torgo, Álvaro Figueira, Nuno Guimarães, 2016, KDIR.

Contributions to the Detection of Unreliable Twitter Accounts through Analysis of Content and Behaviour

Luís Torgo, Álvaro Figueira, Nuno Guimarães, 2018, KDIR.

Current State of the Art to Detect Fake News in Social Media: Global Trendings and Next Challenges

Luís Torgo, Álvaro Figueira, Nuno Guimarães, 2018, WEBIST.

Rule-Based Prediction of Rare Extreme Values

Luís Torgo, Rita P. Ribeiro, L. Torgo, 2006, Discovery Science.

Random Decision Forests

Risto Miikkulainen, Johannes Fürnkranz, Jun Morimoto, 2010, Encyclopedia of Machine Learning.

Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases

Luís Torgo, João Gama, Rui Camacho, 2005 .

Resource-Bounded Fraud Detection

Luís Torgo, L. Torgo, 2007, EPIA Workshops.

Controlled Redundancy in Incremental Rule Learning

Luís Torgo, L. Torgo, 1993, ECML.

Guided Self Training for Sentiment Classification

Luís Torgo, Brett Drury, José João Almeida, 2011 .

Dynamic Discretization of Continuous Attributes

Luís Torgo, João Gama, Carlos Soares, 1998, IBERAMIA.

Classifying News Stories with a Constrained Learning Strategy to Estimate the Direction of a Market Index

Luís Torgo, Brett Drury, José João Almeida, 2012, Int. J. Comput. Sci. Appl..

Predicting Wildfires - Propositional and Relational Spatio-Temporal Pre-processing Approaches

Luís Torgo, Mariana Oliveira, Vítor Santos Costa, 2016, DS.

The CURE for Class Imbalance

Luís Torgo, Paula Branco, Colin Bellinger, 2019, DS.

Receiver Operating Characteristic Analysis

Risto Miikkulainen, Johannes Fürnkranz, Luís Torgo, 2010, Encyclopedia of Machine Learning.

Resampling Approaches to Improve News Importance Prediction

Luís Torgo, Nuno Moniz, Fátima Rodrigues, 2014, IDA.

A Comparative Study of Reliable Error Estimators for Pruning Regression Trees

Luís Torgo, L. Torgo, 2007 .

OpenML: A Collaborative Science Platform

Luís Torgo, Bernd Bischl, Bo Gao, 2013, ECML/PKDD.

Knowledge-based Reliability Metrics for Social Media Accounts

Luís Torgo, Álvaro Figueira, Nuno Guimarães, 2020, WEBIST.

Mean Squared Error

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning.

Clustered Partial Linear Regression

Luís Torgo, Joaquim Pinto da Costa, 2000, ECML.

UBL: an R package for Utility-based Learning pdf

Luís Torgo, Rita P. Ribeiro, Paula Branco, 2016, ArXiv.

Arbitrated Ensemble for Solar Radiation Forecasting

Luís Torgo, Carlos Soares, Vítor Cerqueira, 2017, IWANN.

Model Trees

Luís Torgo, 2010, Encyclopedia of Machine Learning.

Contributions to the Detection of Unreliable Twitter Accounts through Analysis of Content and Behaviour.

Luís Torgo, Álvaro Figueira, Nuno Guimarães, 2018 .

Multistrategy Ensemble Learning

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning.

Visual interpretation of regression error

Inês Areosa, Luís Torgo, 2020, Expert Syst. J. Knowl. Eng..

YAILS an incremental learning program

Luís Torgo, 1992 .

Adapting Peepholing to Regression Trees

Luís Torgo, Joana Marques, 2005, EPIA.

A Comparative Study of Performance Estimation Methods for Time Series Forecasting

Luís Torgo, Igor Mozetic, Jasmina Smailovic, 2017, 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

2D-interval predictions for time series

Luís Torgo, Orlando Ohashi, L. Torgo, 2011, KDD.

Predicting Harmful Algae Blooms

Luís Torgo, Rita P. Ribeiro, 2003, EPIA.

Computationally Efficient Linear Regression Trees

Luís Torgo, 2002 .

Multi-Armed Bandit

Johannes Fürnkranz, Luís Torgo, Katharina Morik, 2010, Encyclopedia of Machine Learning.

Missing Values

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning.

Multi-Source Social Feedback of Online News Feeds pdf

Luís Torgo, Nuno Moniz, L. Torgo, 2018, ArXiv.

Spatial Interpolation Using Multiple Regression

Luís Torgo, Orlando Ohashi, L. Torgo, 2012, 2012 IEEE 12th International Conference on Data Mining.

An Infra-Structure for Performance Estimation and Experimental Comparison of Predictive Models in R pdf

Luís Torgo, 2014, ArXiv.

Ensembles for Time Series Forecasting

Luís Torgo, Mariana Oliveira, L. Torgo, 2014, ACML.

Evaluation Procedures for Forecasting with Spatio-Temporal Data

Luís Torgo, Mariana Oliveira, Vítor Santos Costa, 2018, ECML/PKDD.

Regression error characteristic surfaces

Luís Torgo, L. Torgo, 2005, KDD '05.

Functional Models for Regression Tree Leaves

Luís Torgo, L. Torgo, Luís Torgo, 1997, ICML.

Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes

Luís Torgo, Carlos Soares, Vítor Cerqueira, 2019, DS.

Data-Driven Relevance Judgments for Ranking Evaluation pdf

Luís Torgo, Nuno Moniz, João Vinagre, 2016, ArXiv.

Wise Sliding Window Segmentation: A classification-aided approach for trajectory segmentation

Luís Torgo, Vania Bogorny, Amílcar Soares Júnior, 2020, Canadian Conference on AI.

SMOGN: a Pre-processing Approach for Imbalanced Regression

Luís Torgo, Rita P. Ribeiro, Paula Branco, 2017, LIDTA@PKDD/ECML.

Constructive Aggregation and Its Application to Forecasting with Dynamic Ensembles

Luís Torgo, Fábio Pinto, Carlos Soares, 2018, ECML/PKDD.

Cost-Sensitive Learning: Preface

Stan Matwin, Luís Torgo, Nuno Moniz, 2018, COST@SDM.

Partial Linear Trees

Luís Torgo, L. Torgo, Luís Torgo, 2000, ICML.

DATA FITTING WITH RULE-BASED REGRESSION

Luís Torgo, L. Torgo, 2007 .

OpenML: networked science in machine learning

Luís Torgo, Bernd Bischl, Joaquin Vanschoren, 2014, SKDD.

A Survey of Predictive Modelling under Imbalanced Distributions pdf

Luís Torgo, Rita P. Ribeiro, Paula Branco, 2015, ArXiv.

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

Luís Torgo, João Gama, Rui Camacho, 2005, PKDD.

Resampling strategies for imbalanced time series forecasting

Luís Torgo, Nuno Moniz, Paula Branco, 2016, International Journal of Data Science and Analytics.

Detecting Errors in Foreign Trade Transactions: Dealing with Insufficient Data

Luís Torgo, Carlos Soares, Welma Pereira, 2009, EPIA.

The Use of Domain Knowledge in Feature Construction for Financial Time Series Prediction

Luís Torgo, Pedro de Almeida, L. Torgo, 2001, EPIA.

A Study on End-Cut Preference in Least Squares Regression Trees

Luís Torgo, L. Torgo, 2001, EPIA.

Machine Learning: ECML 2005, 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings

Luís Torgo, João Gama, Rui Camacho, 2005, ECML.

Precision and Recall for Regression

Luís Torgo, Rita P. Ribeiro, L. Torgo, 2009, Discovery Science.

Resource-bounded Outlier Detection using Clustering Methods

Luís Torgo, Carlos Soares, Carlos Soares, 2010, Data Mining for Business Applications.

Interval Forecast of Water Quality Parameters

Luís Torgo, Rita P. Ribeiro, Orlando Ohashi, 2010, ECAI.

Dynamic and Heterogeneous Ensembles for Time Series Forecasting

Luís Torgo, Mariana Oliveira, Bernhard Pfahringer, 2017, 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Knowledge Integration and Learning

Luís Torgo, Pavel Brazdil, Rua Campo Alegre, 1991 .

Twitter as a Source for Time- and Domain-Dependent Sentiment Lexicons

Luís Torgo, Álvaro Figueira, Nuno Guimarães, 2018, Social Network Based Big Data Analysis and Applications.

KNOWLEDGE INTEGRATION AND FORGETTING

Luís Torgo, 2007 .

Efficient and Comprehensible Local Regression

Luís Torgo, L. Torgo, 2000, PAKDD.

Radial Basis Function Neural Networks

Risto Miikkulainen, Johannes Fürnkranz, Jun Morimoto, 2010, Encyclopedia of Machine Learning.

Arbitrage of forecasting experts

Luís Torgo, Fábio Pinto, Carlos Soares, 2018, Machine Learning.

Clustered Partial Linear Regression

Luís Torgo, Joaquim Pinto da Costa, J. Costa, 2000, Machine Learning.

Data Mining with R: Learning with Case Studies

Luís Torgo, L. Torgo, 2010 .

Regression Trees

Luís Torgo, 2010, Encyclopedia of Machine Learning.

Wind speed forecasting using spatio-temporal indicators

Luís Torgo, Orlando Ohashi, L. Torgo, 2012, ECAI.

Error Estimators for Pruning Regression Trees

Luís Torgo, 1998, ECML.

Predicting the Density of Algae Communities using Local Regression Trees

Luís Torgo, L. Torgo, 2001 .

Proceedings of the 16th European conference on Machine Learning

Luís Torgo, João Gama, Rui Camacho, 2005 .

Learning Through Utility Optimization in Regression Tasks

Luís Torgo, Rita P. Ribeiro, Bernhard Pfahringer, 2017, 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Time-Based Ensembles for Prediction of Rare Events in News Stream

Luís Torgo, Magdalini Eirinaki, Nuno Moniz, 2016, 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW).

Utility-Based Regression

Luís Torgo, Rita P. Ribeiro, L. Torgo, 2007, PKDD.

Pre-processing approaches for imbalanced distributions in regression

Luís Torgo, Rita P. Ribeiro, Paula Branco, 2019, Neurocomputing.

A Contextual Classification Strategy for Polarity Classification of Direct Quotations from Financial News

Luís Torgo, Brett Drury, Gaël Dias, 2011, RANLP 2011.

A review on web content popularity prediction: Issues and open challenges

Luís Torgo, Nuno Moniz, L. Torgo, 2019, Online Soc. Networks Media.

Learning with Imbalanced Domains: Preface

Luís Torgo, Bartosz Krawczyk, Nuno Moniz, 2017, LIDTA@PKDD/ECML.

Arbitrated Ensemble for Time Series Forecasting

Luís Torgo, Fábio Pinto, Carlos Soares, 2017, ECML/PKDD.

Regression by Classification

Luís Torgo, João Gama, João Gama, 1996, SBIA.

OpenML: A Collaborative Science Platform

Luís Torgo, Bernd Bischl, Bo Gao, 2013, ECML/PKDD.

Knowledge Acquisition via Knowledge Integration

Luís Torgo, Pavel Brazdil, P. Brazdil, 1990 .

Regression Trees

Luís Torgo, L. Torgo, Luís Torgo, 2010, Encyclopedia of Machine Learning.

2nd Workshop on Learning with Imbalanced Domains: Preface

Stan Matwin, Luís Torgo, Bartosz Krawczyk, 2018, LIDTA@ECML/PKDD.

REBAGG: REsampled BAGGing for Imbalanced Regression

Luís Torgo, Rita P. Ribeiro, Paula Branco, 2018, LIDTA@ECML/PKDD.

Predicting Outliers

Luís Torgo, Rita P. Ribeiro, L. Torgo, 2003, PKDD.

Mean Absolute Error

Johannes Fürnkranz, Luís Torgo, Thomas Stützle, 2010, Encyclopedia of Machine Learning and Data Mining.

Resampling strategies for imbalanced time series forecasting

Luís Torgo, Nuno Moniz, Paula Branco, 2017, International Journal of Data Science and Analytics.

Selection of Table Areas for Information Extraction

Luís Torgo, Alípio Mário Jorge, Ana Costa e Silva, 2003 .

A Framework for Recommendation of Highly Popular News Lacking Social Feedback

Luís Torgo, Magdalini Eirinaki, Nuno Moniz, 2017, New Generation Computing.

Relevance-Based Evaluation Metrics for Multi-class Imbalanced Domains

Luís Torgo, Rita P. Ribeiro, Paula Branco, 2017, PAKDD.

MetaUtil: Meta Learning for Utility Maximization in Regression

Luís Torgo, Rita P. Ribeiro, Paula Branco, 2018, DS.

Class-Based Outlier Detection: Staying Zombies or Awaiting for Resurrection?

Luís Torgo, Lubos Popelínský, Karel Vaculík, 2015, IDA.

Exploring Resampling with Neighborhood Bias on Imbalanced Regression Problems

Luís Torgo, Rita P. Ribeiro, Paula Branco, 2017, EPIA.

Evaluation of Ensemble Methods in Imbalanced Regression Tasks

Luís Torgo, Nuno Moniz, Paula Branco, 2017, LIDTA@PKDD/ECML.

A Survey of Predictive Modeling on Imbalanced Domains

Luís Torgo, Rita P. Ribeiro, Paula Branco, 2016, ACM Comput. Surv..

Automatic Selection of Table Areas in Documents for Information Extraction

Luís Torgo, Alípio Mário Jorge, Ana Costa e Silva, 2003, EPIA.

SMOTE for Regression

Luís Torgo, Rita P. Ribeiro, Bernhard Pfahringer, 2013, EPIA.

Active Learning for Imbalanced Domains: the ALOD and ALOD-RE Algorithms

Luís Torgo, Paula Branco, Mayukh Bhattacharjee, 2021, 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA).

Evaluation Procedures for Forecasting with Spatiotemporal Data

Luís Torgo, Vítor Santos Costa, Mariana Oliveira, 2021 .

Biased resampling strategies for imbalanced spatio-temporal forecasting

Luís Torgo, Nuno Moniz, Mariana Oliveira, 2021, Int. J. Data Sci. Anal..

Towards a pragmatic detection of unreliable accounts on social networks

Luís Torgo, Álvaro Figueira, Nuno Guimarães, 2021, Online Soc. Networks Media.

An organized review of key factors for fake news detection pdf

Luís Torgo, Álvaro Figueira, Nuno Guimarães, 2021, ArXiv.

Kernel Regression Trees

Luís Torgo, L. Torgo, 2007 .

Improvement of News Ranking through Importance Prediction [ Extended

Luís Torgo, Nuno Moniz, Roberto Frias, 2014 .

LIACC Machine Learning group Internal Report n . 98-1 Sequence-based Methods for Pruning Regression Trees

Luís Torgo, 1998 .

Clustered Multiple Regression

Luís Torgo, L. Torgo, J. M. C. D. Costa, 2000 .