Abstract Machine Learning (ML) algorithms have been increasingly replacing people in
several application domains—in which the majority suffer from data imbalance. In order to …

Since most classifiers are biased toward the dominant class, class imbalance is a
challenging problem in machine learning. The most popular approaches to solving this …

The paper deals with traffic prediction that can be done in intelligent transportation systems
which involve the prediction between the previous year's dataset and the recent year's data …

Since last two decades, imbalanced data is becoming a hot topic to do research or to
determine meaningful results. One of the problems of machine learning and data mining …

Encrypted domain name resolution can reduce the risk of privacy leakage for Internet users.
However, it may also prevent network administrators from detecting suspicious …

In an era characterized by the proliferation of digital media, the need to efficiently use
multimedia content has become paramount. This article discusses an innovative technique …

In this study, we propose an adaptive fuzzy weight algorithm for the problem of two-class
imbalanced learning. Initially, our algorithm finds a set of fuzzy weight values for data …

Thermocouples and vibration sensors were set up on a Fused Deposition Modeling
Manufacturing machine, where the extruder temperature, bed temperature and extruder …

Outliers are eccentric data points with anomalous nature. Clustering with outliers has
received a lot of attention in the data processing community. But, they inordinately affect the …

This paper introduces a traffic prediction system for intelligent transportation, leveraging
machine learning and regression models, specifically emphasizing Gated Recurrent Unit …