Publikationen, an denen er mitarbeitet Chris Cornelis (19)

2018

  1. Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach

    Knowledge and Information Systems, Vol. 56, Núm. 1, pp. 55-84

  2. Multi-label classification using a fuzzy rough neighborhood consensus

    Information Sciences, Vol. 433-434, pp. 96-114

2016

  1. Evolutionary wrapper approaches for training set selection as preprocessing mechanism for support vector machines: Experimental evaluation and support vector analysis

    Applied Soft Computing Journal, Vol. 38, pp. 10-22

  2. Fuzzy multi-instance classifiers

    IEEE Transactions on Fuzzy Systems, Vol. 24, Núm. 6, pp. 1395-1409

  3. Fuzzy rough classifiers for class imbalanced multi-instance data

    Pattern Recognition, Vol. 53, pp. 36-45

  4. Fuzzy-rough imbalanced learning for the diagnosis of High Voltage Circuit Breaker maintenance: The SMOTE-FRST-2T algorithm

    Engineering Applications of Artificial Intelligence, Vol. 48, pp. 134-139

  5. Multiple instance learning: Foundations and algorithms

    Springer International Publishing, pp. 1-233

2015

  1. Evolutionary undersampling for imbalanced big data classification

    2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings

  2. IFROWANN: Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor Classification

    IEEE Transactions on Fuzzy Systems, Vol. 23, Núm. 5, pp. 1622-1637

2014

  1. A multi-instance learning wrapper based on the Rocchio classifier for web index recommendation

    Knowledge-Based Systems, Vol. 59, pp. 173-181

  2. Implementing algorithms of rough set theory and fuzzy rough set theory in the R package "roughSets"

    Information Sciences, Vol. 287, pp. 68-89

  3. Preprocessing noisy imbalanced datasets using SMOTE enhanced with fuzzy rough prototype selection

    Applied Soft Computing Journal, Vol. 22, pp. 511-517

2013

  1. FRPS: A Fuzzy Rough Prototype Selection method

    Pattern Recognition, Vol. 46, Núm. 10, pp. 2770-2782

  2. OWA-FRPS: A prototype selection method based on ordered weighted average fuzzy rough set theory

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. On the use of evolutionary feature selection for improving fuzzy rough set based prototype selection

    Soft Computing, Vol. 17, Núm. 2, pp. 223-238

2012

  1. Enhancing evolutionary instance selection algorithms by means of fuzzy rough set based feature selection

    Information Sciences, Vol. 186, Núm. 1, pp. 73-92

  2. Improving SMOTE with fuzzy rough prototype selection to detect noise in imbalanced classification data

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. SMOTE-FRST: A new resampling method using fuzzy rough set theory

    World Scientific Proc. Series on Computer Engineering and Information Science 7; Uncertainty Modeling in Knowledge Engineering and Decision Making - Proceedings of the 10th International FLINS Conf.

2011

  1. A preliminary study on the use of fuzzy rough set based feature selection for improving evolutionary instance selection algorithms

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)