Logistic regression is a commonly used classification algorithm in machine learning. It
allows categorizing data into discrete classes by learning the relationship from a given set of …

Traffic flow usually contains complex nonlinear patterns. Deep learning can model nonlinear
fluctuations through iterative updates of trainable parameters. It generally requires a large …

For class-imbalance problems, traditional supervised learning algorithms tend to favor
majority instances (also called negative instances). Therefore, it is difficult for them to …

This article considers the parameter estimation problems for the controlled autoregressive
systems interfered by moving average noises. A recursive extended gradient algorithm with …

Support Vector Machines (SVMs) are a type of supervised machine learning algorithm
widely used for classification tasks. In contrast to traditional methods that split the data into …

Support vector machine (SVM) is a popular binary classification algorithm widely utilized in
various fields due to its accuracy and versatility. However, most of the existing research …

Dissolved oxygen (DO) concentration in aquatic systems plays a vital role in water
aquaculture. An innovative approach that combines feature selection and ensemble …

Monitoring valve operation status is very significant in saving natural gas resources and
realizing sustainability of the fossil energy. At present, many machine learning algorithms …

The capability to accurately detect web application attacks, especially in a timely fashion, is
crucial but remains an ongoing challenge. This study provides an in-depth evaluation of 19 …

Support vector classification (SVC) is a well-known statistical technique for classification
problems in machine learning and other fields. An important question for SVC is the …