The feature selection is an essential data preprocessing stage in data mining. The core
principle of feature selection seems to be to pick a subset of possible features by excluding …

Feature selection aims at finding the minimum number of features that result in high
classification accuracy. Accordingly, the feature selection is considered as a multi-objective …

Feature selection plays a pivotal role in machine learning, serving as a critical
preprocessing step. Its impact extends beyond enhancing the classification capabilities of …

Abstract The Evaluation of Text Summaries (ETS) has been a task of constant challenges to
the development of Automatic Text Summarization (ATS). Within the ATS task, the ETS is …

Fast and precise medical diagnosis of human cancer is crucial for treatment decisions. Gene
selection consists of identifying a set of informative genes from microarray data to allow high …

Feature selection, a method of dimensionality reduction, is nothing but collecting a range of
appropriate feature subsets from the total number of features. In this paper, a point by point …

Three-phase transformers (TPT) play a significant and crucial function in the power networks
in order to connect the sub-systems and deliver the electrical energy to final customers. The …

The goal of this article is to present a new hybrid technique for solving the feature selection
problem. Conventionally, the process of determining the most relevant subset based on the …

Breast cancer is a widespread and serious condition that poses a significant threat to
women's health globally, contributing significantly to mortality rates. Machine learning tools …

In this study, we propose a Binary Particle Swarm Optimization algorithm hybridizing with
Oppositionbased Learning for solving the feature selection problem. Opposition-based …