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Learning rules for multi-label classification: a stacking and a separate-and-conquer approach

Machine learning, 2016-10, Vol.105 (1), p.77-126

2016

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A flexible class of dependence-aware multi-label loss functions

Machine learning, 2022-02, Vol.111 (2), p.713-737

2022

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A rapid-prototyping framework for extracting small-scale incident-related information in microblogs: Application of multi-label classification on tweets

Information systems (Oxford), 2016-04, Vol.57, p.88-110

2016

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Re-training Deep Neural Networks to Facilitate Boolean Concept Extraction

Discovery Science, p.127-143

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Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain

Machine Learning and Knowledge Discovery in Databases, p.50-65

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Correlation-Based Discovery of Disease Patterns for Syndromic Surveillance

Frontiers in big data, 2022-01, Vol.4, p.784159-784159

2022

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Efficient voting prediction for pairwise multilabel classification

Neurocomputing (Amsterdam), 2010-03, Vol.73 (7), p.1164-1176

2010

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DeepRED – Rule Extraction from Deep Neural Networks

Discovery Science, p.457-473

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Tree-based dynamic classifier chains

Machine learning, 2023-11, Vol.112 (11), p.4129-4165

2023

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Multilabel classification via calibrated label ranking

Machine learning, 2008-11, Vol.73 (2), p.133-153

2008

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Stacking Label Features for Learning Multilabel Rules

Discovery Science, p.192-203

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Comparing Boosting and Bagging for Decision Trees of Rankings

Journal of classification, 2022-03, Vol.39 (1), p.78-99

2022

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Efficient Discovery of Expressive Multi-label Rules Using Relaxed Pruning

Discovery Science, p.367-382

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A Unifying Framework and Comparative Evaluation of Statistical and Machine Learning Approaches to Non-Specific Syndromic Surveillance

Computers (Basel), 2021-03, Vol.10 (3), p.32

2021

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Combining Predictions Under Uncertainty: The Case of Random Decision Trees

Discovery Science, p.78-93

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Revisiting Non-specific Syndromic Surveillance

Advances in Intelligent Data Analysis XIX, p.128-140

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Sum-Product Networks for Early Outbreak Detection of Emerging Diseases

Artificial Intelligence in Medicine, p.61-71

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Analysis and Optimization of Deep Counterfactual Value Networks

KI 2018: Advances in Artificial Intelligence, p.305-312

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Rule-Based Multi-label Classification: Challenges and Opportunities

Rules and Reasoning, p.3-19

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On the Trade-Off Between Consistency and Coverage in Multi-label Rule Learning Heuristics

Discovery Science, p.96-111

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Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules

Advances in Knowledge Discovery and Data Mining, p.29-42

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A Hybrid Multi-strategy Recommender System Using Linked Open Data

Semantic Web Evaluation Challenge, p.150-156

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Pairwise learning of multilabel classifications with perceptrons

2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), 2008, Vol.10, p.2899-2906

2008

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Gradient-Based Label Binning in Multi-label Classification

Machine Learning and Knowledge Discovery in Databases. Research Track, p.462-477

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Learning Gradient Boosted Multi-label Classification Rules

Machine Learning and Knowledge Discovery in Databases, p.124-140

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Learning rules for multi-label classification: a stacking and a separate-and-conquer approach

A flexible class of dependence-aware multi-label loss functions

A rapid-prototyping framework for extracting small-scale incident-related information in microblogs: Application of multi-label classification on tweets

Re-training Deep Neural Networks to Facilitate Boolean Concept Extraction

Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain

Correlation-Based Discovery of Disease Patterns for Syndromic Surveillance

Efficient voting prediction for pairwise multilabel classification

DeepRED – Rule Extraction from Deep Neural Networks

Tree-based dynamic classifier chains

Multilabel classification via calibrated label ranking

Stacking Label Features for Learning Multilabel Rules

Comparing Boosting and Bagging for Decision Trees of Rankings

Efficient Discovery of Expressive Multi-label Rules Using Relaxed Pruning

A Unifying Framework and Comparative Evaluation of Statistical and Machine Learning Approaches to Non-Specific Syndromic Surveillance

Combining Predictions Under Uncertainty: The Case of Random Decision Trees

Revisiting Non-specific Syndromic Surveillance

Sum-Product Networks for Early Outbreak Detection of Emerging Diseases

Analysis and Optimization of Deep Counterfactual Value Networks

Rule-Based Multi-label Classification: Challenges and Opportunities

On the Trade-Off Between Consistency and Coverage in Multi-label Rule Learning Heuristics

Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules

A Hybrid Multi-strategy Recommender System Using Linked Open Data

Pairwise learning of multilabel classifications with perceptrons

Gradient-Based Label Binning in Multi-label Classification

Learning Gradient Boosted Multi-label Classification Rules

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