This paper presents a new feature-selection approach based on the cuttlefish optimization
algorithm which is used for intrusion detection systems (IDSs). Because IDSs deal with a …

Feature selection is an important task for data analysis and information retrieval processing,
pattern classification systems, and data mining applications. It reduces the number of …

The rapid growth in web development has transformed today's communication. The
combination of features and corresponding sentiment words (SWs) can help produce …

Feature selection and feature extraction are the most important steps in classification
systems. Feature selection is commonly used to reduce dimensionality of datasets with tens …

Feature selection is a process of selecting optimal features that produce the most prognostic
outcome. It is one of the essential steps in knowledge discovery. The crisis is that not all …

Protein function prediction is an important problem in functional genomics. Typically, protein
sequences are represented by feature vectors. A major problem of protein datasets that …

Plant diseases is one of the major bottlenecks in agricultural production that have bad
effects on the economic of any country. Automatic detection of such disease could minimize …

Feature selection (FS) is an important task which can significantly affect the performance of
image classification and recognition. In this paper, we present a feature selection algorithm …

Feature selection (FS) is one of the most important fields in pattern recognition, which aims
to pick a subset of relevant and informative features from an original feature set. There are …

Feature selection (FS) and classification are consecutive artificial intelligence (AI) methods
used in data analysis, pattern classification, data mining and medical informatics. Beside …