Clustering is a machine learning paradigm of dividing sample subjects into a number of
groups such that subjects in the same groups are more similar to those in other groups. With …

Abstract Purpose of Review Artificial intelligence (AI) technology holds both great promise to
transform mental healthcare and potential pitfalls. This article provides an overview of AI and …

Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …

In recent years, the appearance of the broad learning system (BLS) is poised to
revolutionize conventional artificial intelligence methods. It represents a step toward building …

High-dimensional data analysis is a challenge for researchers and engineers in the fields of
machine learning and data mining. Feature selection provides an effective way to solve this …

In recent years, unsupervised feature selection methods have raised considerable interest in
many research areas; this is mainly due to their ability to identify and select relevant features …

Among the background of developments in automation and intelligence, machine learning
technology has been extensively applied in aquaculture in recent years, providing a new …

Major assumptions in computational intelligence and machine learning consist of the
availability of a historical dataset for model development, and that the resulting model will, to …

This survey aims at providing a state-of-the-art overview of feature selection and fusion
strategies, which select and combine multi-view features effectively to accomplish …

Big multimedia data is heterogeneous in essence, that is, the data may be a mixture of
video, audio, text, and images. This is due to the prevalence of novel applications in recent …