Scientific Research Publishing

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features ()

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...
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 ...
LinkedIn

Getting Started with Support Vector Machines: Theory and Hands-On Applications

Continuing our machine learning (ML) journey, in this edition we’ll look into Support Vector Machine (SVM). SVM is a powerful and versatile ML model capable of performing both linear or nonlinear ...
Frontiers

A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing (ELSA)

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...
Nature

Intrusion detection system based on machine learning using least square support vector machine

Cyber security faces tremendous hurdles as a result of the rapid development and widespread adoption of technologies like 5G, IoT, cloud computing, and others that have increased network scale, ...
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 ...
Searchenginejournal.com

Introduction To Vector Databases And How To Use AI For SEO

Learn how to use vector databases for AI SEO and enhance your content strategy. Find the closest semantic similarity for your target query with efficient vector embeddings. A vector database is a ...
C&EN

QSAR Classification Modeling Using Machine Learning with a Consensus-Based Approach for Multivariate Chemical Hazard End Points

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. A study by Lou et al. predicting chemical acute dermal toxicity ...
LinkedIn

A Deep Dive into Support Vector Machines (SVM): The Power of Precise Classification

In the ever-evolving field of machine learning, Support Vector Machines (SVM) have earned their place as one of the most reliable algorithms for classification and regression tasks. Known for their ...
Nature

An enhanced approach for predicting air pollution using quantum support vector machine

The essence of quantum machine learning is to optimize problem-solving by executing machine learning algorithms on quantum computers and exploiting potent laws such as superposition and entanglement.