Class imbalance Learning (CIL) is an important machine learning branch. Due to an
imbalanced dataset, the efficiency of the classifiers is impacted. Various under/oversampling …

A very crucial branch of Natural Language Processing is Sentiment Analysis, which seeks to
elicit feelings in the public from feedback provided by users. This study proposes a …

Purpose Hate speech is an expression of intense hatred. Twitter has become a popular
analytical tool for the prediction and monitoring of abusive behaviors. Hate speech detection …

Purpose In order to improve the weak recognition accuracy and robustness of the
classification algorithm for brain-computer interface (BCI), this paper proposed a novel …

This study examines the relationship between macroeconomic variables and stock price
indices of four prominent OPEC oil-exporting members. Bayesian model averaging (BMA) …

The purpose of this paper is to propose new predictive maintenance (PdM) framework that
has three aims: 1) estimating the remaining useful life (RUL) of a machine; 2) classifying …

The quality of the data space, which is often represented by a set of features, is one of the
most critical aspects affecting the classification performance of a machine learning …

The state-owned assets portfolio problem is a nonlinear programming problem, and the
traditional algorithm can not effectively find the optimal solution, so the effective solution has …

Class imbalance learning (CIL) is an important machine learning branch. Due to an
imbalanced dataset, the efficiency of the classifiers is impacted. Various under/oversampling …

The block Matching method is an extremely robust and efficient approach for motion
estimation of video sequences. For motion estimation, evolutionary algorithms are being …