Frontiers

Retrieving interpretability to support vector machine regression models in dynamic system identification

Interpretability of Support Vector Machine (SVM) or Neural Networks (NN) models, examples of black-box models, is a field of study that has recently gained attention, especially for the significant ...
Beebom

AI vs Machine Learning: What is the Difference?

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
IEEE

Support Vector Machine-Integrated High-Definition MCPWM Technique for Improving Power Quality in Multilevel Inverters

Abstract: What if machine learning could predict inverter harmonics before prototyping? Conventional pulse width modulation (PWM) techniques in cascaded H-bridge (CHB) multilevel inverters (MLIs) ...
Frontiers

Assessing the learning potential of freshmen in labor education courses using ordinal features and support vector machine

Introduction: Artificial intelligence (AI) marks a new wave of the information technology revolution and permeates various sectors as an indispensable tool. Despite its widespread adoption, its ...
GitHub

Prediction of stroke using Support Vector Machine (SVM) and Decision Tree (DTREE).

The stroke deprives person's brain of oxygen and nutrients, which can cause brain cells to die. Numerous works have been carried out for predicting various diseases by comparing the performance of ...
IEEE

FASTEN: Fuzzy Neural Support Vector Machine for Classification

Abstract: 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 ...
Scientific Research Publishing

Huang, X.L., Shi, L. and Suykens, J.A.K. (2014) Support Vector Machine Classifier with Pinball Loss. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36, 984-997.

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 ...
Scientific Research Publishing

Guido, R., Ferrisi, S., Lofaro, D., & Conforti, D. (2024). An Overview on the Advancements of Support Vector Machine Models in Healthcare Applications: A Review. Information ...

ABSTRACT: Background and Theoretical Dilemma: The United States of America (USA) is the world’s largest consumer of crude oil in the world. Ensuring the sustainability of the role of crude oil in the ...
C&EN

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

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.