Feature selection (FS), as one of the most significant preprocessing techniques in the fields
of machine learning and pattern recognition, has received great attention. In recent years …

Feature selection (FS) constitutes a series of processes used to decide which relevant
features/attributes to include and which irrelevant features to exclude for predictive …

The scientific field of optimization has witnessed an increasing trend in the development of
metaheuristic algorithms within the current decade. The vast majority of the proposed …

Ubiquitous system returns to making pervasive computing in daily lives, the objects of smart
environment becomes intelligent and interconnect without anyone being conscious of the …

Recently, long short‐term memory (LSTM) networks are extensively utilized for text
classification. Compared to feed‐forward neural networks, it has feedback connections, and …

In the realm of high‐dimensional data analysis, numerous fields stand to benefit from its
applications, including the biological and medical sectors that are crucial for computer …

A huge amount of data has been generated over the internet since few decades which is
increasing exponentially. It has become difficult to manually classify the online and offline …

In text classification, it is necessary to perform feature selection to alleviate the curse of
dimensionality caused by high-dimensional text data. In this paper, we utilize class term …

A substantial portion of today's multimedia data exists in the form of unstructured text.
However, the unstructured nature of text poses a significant task in meeting users' …

Document classification is becoming increasingly essential for the vast number of
documents available in digital libraries, emails, the Internet, etc. Textual records frequently …