GitHub

Machine Learning spam classifier achieving 98% accuracy using SVM, NLP, and TF-IDF vectorization

An intelligent spam detection system that classifies SMS/email messages with 98.48% accuracy using machine learning. This project compares multiple algorithms and provides comprehensive performance ...
IEEE

A Novel Method to Enhance the Kernel Matrix of Support Vector Machine Classifier Using Genetic Algorithm for Intrusion Detection System

Abstract: Support vector machine (SVM) is a notable classification algorithm in the application of intrusion detection system (IDS). It achieves high accuracy in categorizing network traffic as normal ...
Frontiers

KDDC: a new framework that integrates kmers, dataset filtering, dimension reduction and classification algorithms to achieve immune cell heterogeneity classification

Introduction: Integrating immune repertoire sequencing data with single cell sequencing data offers profound insights into the diversity of immune cells and their dynamic changes across various ...
Frontiers

Migraine triggers, phases, and classification using machine learning models

1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
Scientific Research Publishing

Comparative Analysis of Machine Learning Algorithms for Optimal Land Use and Land Cover Classification: Guiding Method Selection for Resource-Limited Settings in Tiaty, Baringo ...

Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral and ...
Scientific Research Publishing

Hybrid Software Model for Defect Detection and Cost Evaluation Using Support Vector Machine Algorithm ()

Software defect prediction and cost estimation are critical challenges in software engineering, directly influencing software quality and project management efficiency. This study presents a ...
IEEE

Khatri-Rao Factorization Based Bi-Level Support Vector Machine for Hyperspectral Image Classification

Abstract: As a benchmark supervised learning algorithm, support vector machine (SVM) has drawn much attention and reported plenty of impressive results in hyperspectral images (HSIs) classification.