Abstract: General twin support vector machine with pinball loss function uses pinball loss function which produce noise insensitivity and resampling stability. However, Pin-GTSVM gives same weights to ...

Given the rapidly evolving landscape of Artificial Intelligence, one of the biggest hurdles tech leaders often come across is ...

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 ...

Our study focused on using the Big Five personality inventory to predict traits from students' smartphone sensor data collected over 2 months under the Horizon Europe project. Through correlation ...

Background: Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging ...

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 ...

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 ...

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.

Abstract: The twin support vector machine (TWSVM) classifier and its fuzzy variant fuzzy twin support vector machine (FTSVM) have received considerable attention due to their low computational ...