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 ...
Department of Chemistry, University of Illinois at Urbana─Champaign, Urbana, Illinois 61801, United States Department of Chemistry, Rice University, Houston, Texas 77005, United States Department of ...
This project was developed as part of my Master's programm at Heilbronn University. The goal is to classify different oil samples (e.g. olive oil, sunflower oil) based on their fluorescence and ...
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 ...
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 ...
ABSTRACT: Making the distinction between different plantation tree species is crucial for creating reliable and trustworthy information, which is critical in forestry administration and upkeep. Over ...
Introduction: Lung cancer is one of the main causes of the rising death rate among the expanding population. For patients with lung cancer to have a higher chance of survival and fewer deaths, early ...
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 ...
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