ListarProducción Científica por tema "Multi-label learning"
Mostrando ítems 1-5 de 5
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Distributed multi-label learning on Apache Spark
(Universidad de Córdoba, UCOPress, 2019)This thesis proposes a series of multi-label learning algorithms for classication and feature selection implemented on the Apache Spark distributed computing model. Five approaches for determining the optimal architecture ... -
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 ... -
LAIM discretization for multi-label data
(2017)Multi-label learning is a challenging task in data mining which has attracted growing attention in recent years. Despite the fact that many multi-label datasets have continuous features, general algorithms developed specially ... -
MIML library: a Modular and Flexible Library for Multi-instance Multi-label Learning
(Elsevier, 2022)MIML library is a Java software tool to develop, test, and compare classification algorithms for multi-instance multi-label (MIML) learning. The library includes 43 algorithms and provides a specific format and facilities ... -
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. ...