Classification tasks have long been a central concern in the field of machine learning. Although deep neural network-based approaches offer a novel, versatile, and highly precise solution for ...

The paper presents a new framework for complex support vector regression (SVR) as well as Support Vector Machines (SVM) for quaternary classification. The method exploits the notion of widely linear ...

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML ...

Machine learning models analyze complex patterns within medical datasets, enabling precise prediction and classification of diseases like CHD [14]- [18]. This study explores the application of three ...

This project implements the Support Vector Machine (SVM) algorithm for predicting user purchase classification. The goal is to train an SVM classifier to predict whether a user will purchase a ...

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 ...

This repository demonstrates the usage of a Support Vector Machine and a Multi-Layer Perceptron Model to detect credit card fraud using MATLAB and Python for pre-processing.