The random k-labelsets ensemble (RAkEL) is a multi-label learning strategy that integrates many single-label learning models. Each single-label model is ...
Active k-Labelsets Ensemble for Multi-label Classification
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A simple yet effective multilabel learning method, called label powerset (LP), considers each distinct combination of labels that exist in the training set as a ...
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Abstract. The random k-labelsets ensemble (RAkEL) is a multi-label learning strategy that integrates many single-label learning models.
Jan 1, 2021 · The random k-labelsets ensemble (RAkEL) is a multi-label learning strategy that integrates many single-label learning models. Each single-label ...
A new fast algorithm for RAkEL, where each training instance is assigned to a small number of models and LP is applied for each model with only the assigned ...
Dec 14, 2022 · Another algorithm of note is the RAndom k-labELsets (RAkEL) [19], which constructed ensembles by training single-label learning models on random ...
In this paper, we study the problem of multi-label ensemble learning. Specifically, we aim at improving the generalization ability of multi-label learning ...
Jul 31, 2023 · Active k-label sets ensemble for multi-label classification. Pattern Recognit. 2021;109:107583. doi: 10.1016/j.patcog.2020.107583. [CrossRef] ...
... Ensemble for Multi-label Classification (GOOWE-ML) is proposed. ... active learning". ... Random k-labelsets: An ensemble method for multilabel classification (PDF) ...
Abstract—Label powerset (LP) method is one category of multi-label learning algorithm. This paper presents a basis expansions model.
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