In high-dimensional data classification, effectively extracting discriminative features while
eliminating redundancy is crucial for enhancing the performances of classifiers, such as …

In multi-instance nonparallel plane learning (NPL), the training set is comprised of bags of
instances and the nonparallel planes are trained to classify the bags. Most of the existing …

Abstract Randomized-based Feedforward Neural Networks approach regression and
classification (binary and multi-class) problems by minimizing the same optimization …

The kernel method is a tool that converts data to a kernel space where operation can be
performed. When converted to a high-dimensional feature space by using kernel functions …

Broad learning system (BLS) is a breadth-based learning algorithm based on single-layer
feedforward network (SLFN), which has the advantages of incremental learning with its fast …

Discrimination problems are of significant interest in the machine learning literature. There
has been growing interest in extending traditional vector-based machine learning …

The support vector machine (SVM) is a powerful tool for pattern classification thanks to its
outstanding efficiency. However, when encountering extensive classification tasks, the …

Though there are several dozens of nonparallel support vector machines (NSVMs), little
studies on general forms and characteristics of NSVMs are investigated. To fill in this gap …

In harsh and complex aerospace environments, stress concentration causes fatigue cracks
to easily form at the edges of rivet holes in an aircraft fuselage, threatening overall aircraft …