Abstract: Supervised learning approaches are widely used for driving style classification; however, they often require a large amount of labeled training data, which is usually scarce in a real-world ...

ABSTRACT: Based on Sentinel-2 satellite data, this study conducted remote sensing inversion of chemical elements in Laguocuo Salt Lake, Xizang, in order to reveal the spatial distribution ...

Support Vector Machines (SVMs) are a powerful machine learning algorithm commonly used for classification tasks. In this article, we'll explore how to apply SVM to classify images, specifically ...

B-type stars and hot subdwarf stars are both intriguing objects in the field of astronomy. B-type stars, also identified as main-sequence B stars, represent a subset of massive, young stars currently ...

Abstract: We propose a novel nonparallel classifier, called nonparallel support vector machine (NPSVM), for binary classification. Our NPSVM that is fully different from the existing nonparallel ...

With the developments in the Information Technology and improvements in the communication channels, fraud is spreading all over the world, resulting in huge financial losses. Though fraud prevention ...

The rock mass is a concrete manifestation of the non-linear coupling of multiple factors in complex rock systems, which is directly related to the selection of construction design parameters and ...

Machine learning is a branch of artificial intelligence that includes methods, or algorithms, for automatically creating models from data. Unlike a system that performs a task by following explicit ...

A support vector machine (SVM) is a software system that can perform binary classification. For example, you can use an SVM to create a model that predicts the sex of a person (male, female) based on ...

In computational chemistry and chemoinformatics, the support vector machine (SVM) algorithm is among the most widely used machine learning methods for the identification of new active compounds. In ...