Abstract Multi-Source Information Fusion (MSIF) is a comprehensive and interdisciplinary
subject, and is referred to as, multi-sensor information fusion which was originated in the …

Fuzzy rough set theory is a powerful tool to deal with uncertainty information, which has
been successfully applied to the fields of attribute reduction, rule extraction, classification …

In recent years, feature selection for multilabel classification has attracted attention in
machine learning and data mining. However, some feature selection methods ignore the …

Obtaining informative features is crucial in imbalanced classification. However, existing
neighborhood rough set-based feature selection approaches easily overlook the diversity …

As a cause of interfering with routine activities, freezing of gait (FOG) is a severe syndrome
of Parkinson's disease (PD) and usually performs as an abrupt and momentary inability to …

Feature selection based on neighborhood rough set is a noteworthy step in dealing with
numerical data. Information entropy, proven in many theoretical analysis and practical …

Recently, multilabel classification has generated considerable research interest. However,
the high dimensionality of multilabel data incurs high costs; moreover, in many real …

Feature selection attempts to capture the more discriminative features and plays a significant
role in multilabel learning. As an efficient mathematical tool to handle incomplete and …

Three-way decision provides a new perspective for dealing with uncertainty and complexity
in decision-making problems. However, behaviors of decision-makers may be influenced by …

Feature selection aims to remove irrelevant or redundant features and thereby remain
relevant or informative features so that it is often preferred for alleviating the dimensionality …