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ML-k’sNN: Label Dependent k Values for Multi-Label k-Nearest Neighbor Rule
(MDPI, 2023)
Multi-label classification as a data mining task has recently attracted increasing interest from researchers. Many current data mining applications address problems with instances that belong to more than one category. ...
PARIS: Partial instance and training set selection. A new scalable approach to multi-label classification
(Elsevier, 2023)
Multi-label classification has recently attracted research interest as a data mining task. Many current applications in data mining address problems that have instances belonging to more than one class. This requires the ...
SI(FS)2: Fast simultaneous instance and feature selection for datasets with many features
(Elsevier, 2021)
Data reduction is becoming increasingly relevant due to the enormous amounts of data that are constantly being produced in many fields of research. Instance selection is one of the most widely used methods for this task. ...
Instance selection for multi-label learning based on a scalable evolutionary algorithm
(IEEE, 2021)
Multi-label classification has recently attracted
greater research interest as a data mining task. Many current ap-
plications in data mining address problems having instances that
belong to more than one class, which ...
Cooperative coevolutionary instance selection for multilabel problems
(Elsevier, 2021)
Multilabel classification as a data mining task has recently attracted greater research interest. Many
current data mining applications address problems having instances that belong to more than one
class, which requires ...