Feature subset selection (FSS) has received a great deal of attention in statistics, machine
learning, and data mining. Real world data analyzed by data mining algorithms can involve …

Intrusion detection is a major research problem in network security. Due to the nonlinear
nature of the intrusion attempts, unpredictable behavior of the network traffic and the large …

Network traffic classification is a significant and problematic aspect of network resource
management arising from an investigation of network developments, planning, and design …

Feature selection and feature extraction have always been of utmost importance owing to
their capability to remove redundant and irrelevant features, reduce the vector space size …

This paper presents a review of some of the most recent evolutionary algorithms used for
solving feature selection based upon previously published research on feature selection. In …

Feature selection is the main step in classification systems, a procedure that selects a subset
from original features. Feature selection is one of major challenges in text categorization …

Smart grid systems enhanced the capability of traditional power networks while being
vulnerable to different types of cyber‐attacks. These vulnerabilities could cause attackers to …

In sentiment analysis, the high dimensionality of the feature vector is a key problem because
it can decrease the accuracy of sentiment classification and make it difficult to obtain the …

Sentiment analysis (SA) is a subfield of natural language processing and data mining which
concerns the problem of extracting useful information from users' comments on the Web …

Opinion mining is a subfield of data mining and natural language processing that concerns
with extracting users' opinion and attitude towards products or services from their comments …