Insights into imbalance-aware Multilabel Prototype Generation mechanisms for k-Nearest Neighbor classification in noisy scenarios
Jose J. Valero-Mas, Carlos Penarrubia, Francisco J. Castellanos, Antonio Javier Gallego, and Jorge Calvo-Zaragoza
Pattern Recognition and Artificial Intelligence Group, University of Alicante, Alicante, Spain
Data reduction framework based on Prototype Generation strategies for improving the efficiency in multilabel kNN-based classification scenarios considering the issues of label imbalance and noisy samples
To be published upon acceptance of the work