Technologies have driven big data collection across many fields, such as genomics and
business intelligence. This results in a significant increase in variables and data points …

This paper provides a new approach to feature selection based on the concept of feature
filters, so that feature selection is independent of the prediction model. Data fitting is stated …

This study aims at capturing the influence of driver drowsiness on prevalence of traffic
violations among long-haul truck drivers. The study is based on a roadside survey of 453 …

Abstract Feature Selection and Functional Data Analysis are two dynamic areas of research,
with important applications in the analysis of large and complex data sets. Straddling these …

Feature selection is an important filtering method for data analysis, pattern classification,
data mining, and so on. Feature selection reduces the number of features by removing …

Neural network structures have a critical impact on the accuracy and stability of forecasting.
Neural architecture search procedures help design an optimal neural network according to …

This study focuses on accrual-based earnings management. The purpose of this study is to
establish an innovative and high-accuracy model for detecting earnings management using …

This paper investigates dimensionality reduction problem for signal decoding. Its main
application is brain–computer interface modeling. The challenge is high redundancy in the …

This study presents a novel Equiangular Direction Method (EDM) to solve a multi-objective
optimization problem. We consider optimization problems, where multiple differentiable …

The paper addresses the problem of designing Brain-Computer Interfaces. It investigates
feature selection methods in regression, applied to ECoG-based motion decoding. The …