IEEE

Unified Twin Support Vector Machines for Large-Scale Pattern Classification

Abstract: Over the years, researchers have proposed numerous Twin Support Vector Machines (TSVM) variants aimed at addressing diverse challenges. These variants encompass sparse TSVM models, robust ...
Scientific Research Publishing

Wu, Y. and Liu, Y. (2007) Robust Truncated Hinge Loss Support Vector Machines. Journal of the American Statistical Association, 102, 974-983.

ABSTRACT: In the field of machine learning, support vector machine (SVM) is popular for its powerful performance in classification tasks. However, this method could be adversely affected by data ...
Frontiers

Migraine triggers, phases, and classification using machine learning models

In many countries, patients with headache disorders such as migraine remain under-recognized and under-diagnosed. Patients affected by these disorders are often unaware of the seriousness of their ...
Nature

Support Vector Machine Classification Techniques

Support vector machines (SVMs) constitute a class of supervised learning models designed to perform classification by constructing a decision boundary, or hyperplane, that optimally separates data ...
IEEE

Manifold Energy Projection Twin Support Vector Machine for Semi-Supervised Classification

Abstract: The Projection Twin Support Vector Machine (PTSVM) and its variant, the Least Squares PTSVM (LSPTSVM), have demonstrated significant effectiveness in supervised classification tasks due to ...
marktechpost

Support Vector Machine (SVM) Algorithm

Support Vector Machines (SVMs) are a powerful and versatile supervised machine learning algorithm primarily used for classification and regression tasks. They excel in high-dimensional spaces and are ...
The New York Times

Paris Paralympics 2024: How the classification system works

PR1, W1, T51, F58, SL4, KL3, SM11. This is not a test to crack a code. But you will see a series of letter and number combinations while engaging with the Paralympics in Paris. At the Olympics, there ...
C&EN

Interpretable AI and Machine Learning Classification for Identifying High-Efficiency Donor–Acceptor Pairs in Organic Solar Cells

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. To enhance the efficiency of organic solar cells, accurately predicting the efficiency ...
Scientific Research Publishing

Ghosh, S., Dasgupta, A. and Swetapadma, A. (2019). A Study on Support Vector Machine Based Linear and Non-Linear Pattern Classification. 2019 International Conference on ...

ABSTRACT: The mango, a fruit of immense economic and dietary significance in numerous tropical and subtropical regions, plays a pivotal role in our agricultural landscape. Accurate identification is ...