Feature selection, as a data preprocessing strategy, has been proven to be effective and
efficient in preparing data (especially high-dimensional data) for various data-mining and …

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 …

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

In many real-world multi-label applications, the content of multi-label data is usually
characterized by high dimensional features, which contains complex correlation information …

Crow search algorithm (CSA) is a new natural inspired algorithm proposed by Askarzadeh
in 2016. The main inspiration of CSA came from crow search mechanism for hiding their …

Purposes To evaluate the capability of PET/CT images for differentiating the histologic
subtypes of non-small cell lung cancer (NSCLC) and to identify the optimal model from …

Abstract Detection of Denial of Service (DoS) attack is one of the most critical issues in cloud
computing. The attack detection framework is very complex due to the nonlinear thought of …

In multi-label learning, objects are essentially related to multiple semantic meanings, and
the type of data is confronted with the impact of high feature dimensionality simultaneously …

Network embedding is to learn low-dimensional vector representations for nodes in a
network. It has shown to be effective in a variety of tasks such as node classification and link …

With the rapid advancement of big data technology, high-dimensional datasets comprising
multi-label data have become prevalent in various fields. However, these datasets often …