Multilabel Classification
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Francisco Charte | Antonio J. Rivera | María José del Jesús | Francisco Herrera | A. J. Rivera | F. Herrera | M. J. D. Jesús | F. Charte | M. J. Jesús
[1] Zhi-Hua Zhou,et al. ML-KNN: A lazy learning approach to multi-label learning , 2007, Pattern Recognit..
[2] Concha Bielza,et al. Multi-label classification with Bayesian network-based chain classifiers , 2014, Pattern Recognit. Lett..
[3] Xindong Wu,et al. Compressed labeling on distilled labelsets for multi-label learning , 2012, Machine Learning.
[4] José Ramón Quevedo,et al. Multilabel classifiers with a probabilistic thresholding strategy , 2012, Pattern Recognit..
[5] Thomas Stützle,et al. Ant Colony Optimization Theory , 2004 .
[6] Grigorios Tsoumakas,et al. Effective and Efficient Multilabel Classification in Domains with Large Number of Labels , 2008 .
[7] Mohammed J. Zaki,et al. Multi-label Lazy Associative Classification , 2007, PKDD.
[8] Huan Liu,et al. Feature Selection for Classification , 1997, Intell. Data Anal..
[9] Min-Ling Zhang,et al. Ml-rbf: RBF Neural Networks for Multi-Label Learning , 2009, Neural Processing Letters.
[10] H. Hotelling. Relations Between Two Sets of Variates , 1936 .
[11] Alex Alves Freitas,et al. A Genetic Algorithm for Optimizing the Label Ordering in Multi-label Classifier Chains , 2013, 2013 IEEE 25th International Conference on Tools with Artificial Intelligence.
[12] Grigorios Tsoumakas,et al. An Empirical Study of Lazy Multilabel Classification Algorithms , 2008, SETN.
[13] Eyke Hüllermeier,et al. On label dependence in multilabel classification , 2010, ICML 2010.
[14] Zhi-Hua Zhou,et al. Multilabel dimensionality reduction via dependence maximization , 2008, TKDD.
[15] Huan Liu,et al. Semi-supervised Feature Selection via Spectral Analysis , 2007, SDM.
[16] Larry A. Rendell,et al. The Feature Selection Problem: Traditional Methods and a New Algorithm , 1992, AAAI.
[17] Haibo He,et al. Learning from Imbalanced Data , 2009, IEEE Transactions on Knowledge and Data Engineering.
[18] Grigorios Tsoumakas,et al. MULAN: A Java Library for Multi-Label Learning , 2011, J. Mach. Learn. Res..
[19] Newton Spolaôr,et al. A Framework to Generate Synthetic Multi-label Datasets , 2014, CLEI Selected Papers.
[20] Francisco Charte,et al. R Ultimate Multilabel Dataset Repository , 2016, HAIS.
[21] Cândida Ferreira. Gene Expression Programming in Problem Solving , 2002 .
[22] Gert R. G. Lanckriet,et al. Semantic Annotation and Retrieval of Music and Sound Effects , 2008, IEEE Transactions on Audio, Speech, and Language Processing.
[23] David J. Sheskin,et al. Handbook of Parametric and Nonparametric Statistical Procedures , 1997 .
[24] Dae-Won Kim,et al. Mutual Information-based multi-label feature selection using interaction information , 2015, Expert Syst. Appl..
[25] Naonori Ueda,et al. Parametric Mixture Models for Multi-Labeled Text , 2002, NIPS.
[26] Francisco Charte,et al. Working with Multilabel Datasets in R: The mldr Package , 2015, R J..
[27] Francisco Charte,et al. Resampling Multilabel Datasets by Decoupling Highly Imbalanced Labels , 2015, HAIS.
[28] Tommy W. S. Chow,et al. ML-TREE: A Tree-Structure-Based Approach to Multilabel Learning , 2015, IEEE Transactions on Neural Networks and Learning Systems.
[29] Jieping Ye,et al. Hypergraph spectral learning for multi-label classification , 2008, KDD.
[30] R. Fisher. THE STATISTICAL UTILIZATION OF MULTIPLE MEASUREMENTS , 1938 .
[31] Alex Alves Freitas,et al. Data mining with an ant colony optimization algorithm , 2002, IEEE Trans. Evol. Comput..
[32] Eyke Hüllermeier,et al. Label ranking by learning pairwise preferences , 2008, Artif. Intell..
[33] Josef Kittler,et al. Multilabel classification using heterogeneous ensemble of multi-label classifiers , 2012, Pattern Recognit. Lett..
[34] Yanika Kongsorot,et al. Multi-label classification with extreme learning machine , 2014, 2014 6th International Conference on Knowledge and Smart Technology (KST).
[35] Mahesh Panchal,et al. Review on Various Problem Transformation Methods for Classifying Multi-Label Data , 2014 .
[36] A. K. Jain,et al. A critical evaluation of intrinsic dimensionality algorithms. , 1980 .
[37] Bernhard Schölkopf,et al. Kernel Dependency Estimation , 2002, NIPS.
[38] Francisco Charte,et al. MLeNN: A First Approach to Heuristic Multilabel Undersampling , 2014, IDEAL.
[39] Xuesong Yan,et al. Multi-label Classification based on Particle Swarm Algorithm , 2013, 2013 IEEE 9th International Conference on Mobile Ad-hoc and Sensor Networks.
[40] Gustavo E. A. P. A. Batista,et al. Class imbalance revisited: a new experimental setup to assess the performance of treatment methods , 2014, Knowledge and Information Systems.
[41] Francisco Charte,et al. MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation , 2015, Knowl. Based Syst..
[42] Jiebo Luo,et al. Learning multi-label scene classification , 2004, Pattern Recognit..
[43] Jesús Alcalá-Fdez,et al. KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework , 2011, J. Multiple Valued Log. Soft Comput..
[44] Saso Dzeroski,et al. Ensembles of Multi-Objective Decision Trees , 2007, ECML.
[45] Jesse Read,et al. A Pruned Problem Transformation Method for Multi-label Classification , 2008 .
[46] Francisco Herrera,et al. An overview of ensemble methods for binary classifiers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemes , 2011, Pattern Recognit..
[47] Masami Ito,et al. Task decomposition and module combination based on class relations: a modular neural network for pattern classification , 1999, IEEE Trans. Neural Networks.
[48] Andrew K. C. Wong,et al. Classification of Imbalanced Data: a Review , 2009, Int. J. Pattern Recognit. Artif. Intell..
[49] Eyke Hüllermeier,et al. Multilabel classification via calibrated label ranking , 2008, Machine Learning.
[50] Sunita Sarawagi,et al. Discriminative Methods for Multi-labeled Classification , 2004, PAKDD.
[51] Juan Ramón Rico-Juan,et al. Improving kNN multi-label classification in Prototype Selection scenarios using class proposals , 2015, Pattern Recognit..
[52] Saso Dzeroski,et al. Dual Layer Voting Method for Efficient Multi-label Classification , 2011, IbPRIA.
[53] Newton Spolaôr,et al. A Comparison of Multi-label Feature Selection Methods using the Problem Transformation Approach , 2013, CLEI Selected Papers.
[54] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[55] Xin Li,et al. Conditional Restricted Boltzmann Machines for Multi-label Learning with Incomplete Labels , 2015, AISTATS.
[56] Francisco Herrera,et al. An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics , 2013, Inf. Sci..
[57] Grigorios Tsoumakas,et al. Random k -Labelsets: An Ensemble Method for Multilabel Classification , 2007, ECML.
[58] Jason Weston,et al. A kernel method for multi-labelled classification , 2001, NIPS.
[59] Miroslav Kubat,et al. Undersampling Approach for Imbalanced Training Sets and Induction from Multi-label Text-Categorization Domains , 2009, PAKDD Workshops.
[60] Grigorios Tsoumakas,et al. Correlation-Based Pruning of Stacked Binary Relevance Models for Multi-Label Learning , 2009 .
[61] Liang Sun,et al. Multi-Label Dimensionality Reduction , 2013 .
[62] Isabelle Guyon,et al. Multivariate Non-Linear Feature Selection with Kernel Multiplicative Updates and Gram-Schmidt Relief , 2003 .
[63] Geoff Holmes,et al. Classifier chains for multi-label classification , 2009, Machine Learning.
[64] Jessica A. Turner,et al. Automated annotation of functional imaging experiments via multi-label classification , 2013, Front. Neurosci..
[65] Yoav Freund,et al. The Alternating Decision Tree Learning Algorithm , 1999, ICML.
[66] Luca Martino,et al. Scalable multi-output label prediction: From classifier chains to classifier trellises , 2015, Pattern Recognit..
[67] John Langford,et al. Multi-Label Prediction via Compressed Sensing , 2009, NIPS.
[68] Eyke Hüllermeier,et al. Bayes Optimal Multilabel Classification via Probabilistic Classifier Chains , 2010, ICML.
[69] Volker Tresp,et al. Multi-label informed latent semantic indexing , 2005, SIGIR '05.
[70] Josef Kittler,et al. Inverse random under sampling for class imbalance problem and its application to multi-label classification , 2012, Pattern Recognit..
[71] Francisco Charte,et al. Concurrence among Imbalanced Labels and Its Influence on Multilabel Resampling Algorithms , 2014, HAIS.
[72] Peter A. Flach,et al. LaCova: A Tree-Based Multi-label Classifier Using Label Covariance as Splitting Criterion , 2014, 2014 13th International Conference on Machine Learning and Applications.
[73] A. J. Rivera,et al. A First Approach to Deal with Imbalance in Multi-label Datasets , 2013, HAIS.
[74] Sebastián Ventura,et al. Multi-label Classification with Gene Expression Programming , 2009, HAIS.
[75] Jianhua Xu,et al. Fast multi-label core vector machine , 2013, Pattern Recognit..
[76] Min-Ling Zhang,et al. A Review on Multi-Label Learning Algorithms , 2014, IEEE Transactions on Knowledge and Data Engineering.
[77] Igor Kononenko,et al. Estimating Attributes: Analysis and Extensions of RELIEF , 1994, ECML.
[78] Eyke Hüllermeier,et al. Combining Instance-Based Learning and Logistic Regression for Multilabel Classification , 2009, ECML/PKDD.
[79] Francisco Charte,et al. Addressing imbalance in multilabel classification: Measures and random resampling algorithms , 2015, Neurocomputing.
[80] Alberto Maria Segre,et al. Programs for Machine Learning , 1994 .
[81] Ron Kohavi,et al. Wrappers for Feature Subset Selection , 1997, Artif. Intell..
[82] Zhi-Hua Zhou,et al. Multilabel Neural Networks with Applications to Functional Genomics and Text Categorization , 2006, IEEE Transactions on Knowledge and Data Engineering.
[83] Alex Alves Freitas,et al. A new ant colony algorithm for multi-label classification with applications in bioinfomatics , 2006, GECCO.
[84] George Tzanetakis,et al. Musical genre classification of audio signals , 2002, IEEE Trans. Speech Audio Process..
[85] Ramakrishnan Srikant,et al. Fast algorithms for mining association rules , 1998, VLDB 1998.
[86] Mikel Galar,et al. Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches , 2013, Knowl. Based Syst..
[87] Francisco Charte,et al. LI-MLC: A Label Inference Methodology for Addressing High Dimensionality in the Label Space for Multilabel Classification , 2014, IEEE Transactions on Neural Networks and Learning Systems.
[88] Xia Geng. An Improved Multi-label Classification Algorithm BRkNN , 2014 .
[89] Cunhe Li,et al. Improvement of Learning Algorithm for the Multi-instance Multi-label RBF Neural Networks Trained with Imbalanced Samples , 2013, J. Inf. Sci. Eng..
[90] Geoff Holmes,et al. Multi-label Classification Using Ensembles of Pruned Sets , 2008, 2008 Eighth IEEE International Conference on Data Mining.
[91] Piotr Synak,et al. Multi-Label Classification of Emotions in Music , 2006, Intelligent Information Systems.
[92] Sanmay Das,et al. Filters, Wrappers and a Boosting-Based Hybrid for Feature Selection , 2001, ICML.
[93] Everton Alvares Cherman,et al. Incorporating label dependency into the binary relevance framework for multi-label classification , 2012, Expert Syst. Appl..
[94] Hiroshi Motoda,et al. Feature Selection for Knowledge Discovery and Data Mining , 1998, The Springer International Series in Engineering and Computer Science.
[95] Paul Smolensky,et al. Information processing in dynamical systems: foundations of harmony theory , 1986 .
[96] Michel Verleysen,et al. Mutual information-based feature selection for multilabel classification , 2013, Neurocomputing.
[97] Germán Castellanos-Domínguez,et al. Managing Imbalanced Data Sets in Multi-label Problems: A Case Study with the SMOTE Algorithm , 2013, CIARP.
[98] Ken Chen,et al. Efficient Classification of Multi-label and Imbalanced Data using Min-Max Modular Classifiers , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.
[99] Andrew McCallum,et al. Collective multi-label classification , 2005, CIKM '05.
[100] Amanda Clare,et al. Knowledge Discovery in Multi-label Phenotype Data , 2001, PKDD.
[101] Bo Chen,et al. Simplified Constraints Rank-SVM for Multi-label Classification , 2014, CCPR.
[102] Ian T. Jolliffe,et al. Principal Component Analysis , 2002, International Encyclopedia of Statistical Science.
[103] Nitesh V. Chawla,et al. SMOTE: Synthetic Minority Over-sampling Technique , 2002, J. Artif. Intell. Res..
[104] Wenqi Liu,et al. Imbalanced Multi-Modal Multi-Label Learning for Subcellular Localization Prediction of Human Proteins with Both Single and Multiple Sites , 2012, PloS one.
[105] Rémi Gilleron,et al. Learning Multi-label Alternating Decision Trees from Texts and Data , 2003, MLDM.
[106] Yoram Singer,et al. Improved Boosting Algorithms Using Confidence-rated Predictions , 1998, COLT' 98.
[107] Sanjeev Sharma,et al. An Investigation of Fuzzy PSO and Fuzzy SVD Based RBF Neural Network for Multi-label Classification , 2013, SocProS.