… The paper focuses on the methods that have incorporated feature selection in their models
for performance evaluation. The paper also discusses the different datasets of IDS and a …

… To address the threats and security issues faced in complicated WSNs, a novel combined
feature selection method known as the Fast Correlation-based Feature Selection (FCBFS) with …

… in order to optimize learning performance in terms of … the selection approaches, feature
selection can be of three types: filter, wrapper and embedded methods. The filter feature selection …

… This paper aims to design and validate a NIDS model for IoT security. PCA, the univariate …
enhance feature selection. We intend to reduce features to the ten best-performing features in …

… Therefore, using feature selection, which is an effective method … performance of SVP has
a critical research significance. To analyse the impact of feature selection on SVP performance, …

… the negative features are absent from the selected features … feature-skew problem, we apply
a feature selection proposed by Zheng et al. [3] which selects positive and negative features …

… feature selection/reduction. The impacts of pre-processing techniques play an important role
in training a neural network to optimize its performance. … increased performance in accuracy …

… the robust and stable features selection problem, we design robust features selection (RFS) …
is more important as compared to classification algorithm for the optimization of performance…

… method and feature selection method… feature selection steps. Data that were captured
involved data preprocessing and normalization whereas feature selection method involved feature …

… The feature selection method that we propose in this paper finds the globally optimal subset
of relevant features … For evaluating the performance of our feature selection approach, two …