Feature selection has gained much consideration from scholars working in the domain of
machine learning and data mining in recent years. Feature selection is a popular problem in …

Gene expression data classification is an important technology for cancer diagnosis in
bioinformatics and has been widely researched. Due to the large number of genes and the …

Feature selection (FS) methods are necessary to develop intelligent analysis tools that
require data preprocessing and enhancing the performance of the machine learning …

Feature selection is a well-known prepossessing procedure, and it is considered a
challenging problem in many domains, such as data mining, text mining, medicine, biology …

Evolutionary computation is promising in tackling with the feature selection problem, but still
has poor performance in obtaining good feature subset in high-dimensional problems. In …

In recent years, the web phishing attack has become one of the most serious web security
problems, in which the phishers can steal significant financial information about the internet …

Feature selection (FS) aims to identify the most relevant and non-redundant feature subset
for improving the classification accuracy, which is regarded as a NP-hard problem. Some …

Over the last few years, web phishing attacks have been constantly evolving causing
customers to lose trust in e-commerce and online services. Various tools and systems based …

Feature selection is an important task in machine learning. As multi-label classification tasks
appear in various fields, researchers have investigated multi-label feature selection …

Feature selection plays a critical role in classification problems. Feature selection methods
intend to retain relevant features and eliminate redundant features. This work focuses on …