We propose a novel text classification model, which aims to improve the performance of
Arabic text classification using machine learning techniques. One of the effective solutions in …

In this article, an improved nonparallel support vector machine (INPSVM) is proposed for
pattern classification. INPSVM inherits almost all advantages of nonparallel support vector …

Multiple-instance learning (MIL) is a variation of supervised learning, where samples are
represented by labeled bags, each containing sets of instances. The individual labels of the …

The paper proposes a novel approach for learning kernel Support Vector Machines (SVM)
from large scale data with reduced computation time. The proposed approach, termed as …

This paper researches the value of the margin distribution in binary classifier. The central
idea of large margin distribution machine (LDM) is to optimize the margin distribution, such …

In this paper, a novel group tensor decomposition (GTD) method is proposed to alleviate
within-class spectral variation by fully exploit the low-rank property of 3D HSI, which can …

The k-nearest centroid neighbor kNCN classifier is one of the non-parametric classifiers
which provide a powerful decision based on the geometrical surrounding neighborhood …

A convex polyhedron classifier that encloses the minority class using a combination of
hyperplanes is potentially effective in imbalanced classification. To construct an easy-to-use …

The seaport plays a critical role in the global supply chain management. Today, with the
increasing growth of the global containerized trade, many challenges appears for the …

The use of indefinite kernels has attracted many research interests in recent years due to
their flexibility. They do not possess the usual restrictions of being positive definite as in the …