Recently a density peaks based clustering algorithm (dubbed as DPC) was proposed to
group data by setting up a decision graph and finding out cluster centers from the graph fast …

The class imbalance problem is a challenge in supervised classification, since many
classifiers are sensitive to class distribution, biasing their prediction towards the majority …

Recognizing negative and speculative information is highly relevant for sentiment analysis.
This paper presents a machine‐learning approach to automatically detect this kind of …

Contrast pattern-based classifiers are an important family of both understandable and
accurate classifiers. Nevertheless, these classifiers do not achieve good performance on …

Objective. To evaluate the impact of the synthetic minority oversampling technique (SMOTE)
on the performance of probabilistic neural network (PNN), naïve Bayes (NB), and decision …

Background Imbalanced datasets pose significant challenges in predictive modeling,
leading to biased outcomes and reduced model reliability. This study addresses data …

This article reports on designing and implementing a multiclass sentiment classification
approach to handle the imbalanced class distribution of Arabic documents. The proposed …

Border Gateway Protocol (BGP) is the core component of the Internet's routing infrastructure.
Abnormal routing behavior impairs global Internet connectivity and stability. Hence …

The essential step of surrogating algorithms is phase randomizing the Fourier transform
while preserving the original spectrum amplitude before computing the inverse Fourier …

Detecting, analyzing, and defending against cyber threats is an important topic in cyber
security. Applying machine learning techniques to detect such threats has received …