… This paper investigates multi-label feature selection problem in the causal perspective.
We study the causal structure of multi-label data, and discover that strong label rel- …

… we investigate multi-label feature selection from a causal perspective, labels and features can
be … Finally, we propose a causality-based multi-label feature selection algorithm. The main …

… scenarios and have not addressed causal relationships between labels … features, and
features and features. Therefore, this paper proposes a novel causal multi-label feature selection …

… To address the above problems, we propose an ensemble causal feature selection method
… ) for multi-label data. First, the causal relationship between labels and features is analyzed …

… multilabel feature selection approaches mainly either explore the feature–label and
feature–feature … article, we formulate multilabel feature selection as a local causal structure …

… algorithms cannot directly address multi-source heterogeneous distribution feature … of causal
invariance in causal inference. Firstly, we formulate the multi-label causal feature selection …

… existing research on multi-label feature selection into six aspects … comparisons on practical
multi-label learning datasets to … We discuss the application of multi-label feature selection in …

… is not about multi-label feature selection. Multi-label feature selection focuses on processing
… domain, multi-label causal feature selection addresses multi-label datasets, allowing for …

… multi-label feature selection problem. Lin and Hu also presented many excellent entropy-based
multi-label feature selection … to select the superior feature subset for multi-label learning. …

… a novel approach called Stable Feature analysis for Causal Multi Label (SFCML), which …
causal feature selection method named SFCML (Stable Feature analysis for Causal Multi Label…