IEEE

Enhancing Alzheimer's Disease Detection Using Optimized Attribute Selection and Random Forest Classifier for Improved Accuracy

Abstract: This research aims at improving the identification of Alzheimer's dementia by using the optimized attribute selection method and preliminary diagnosis data-driven learning algorithm, namely ...
IEEE

GWO-Boosted Multi-Attribute Client Selection for Over- The-Air Federated Learning

Abstract: Federated Learning (FL) has gained popularity across various industries due to its ability to train machine learning models without explicit sharing of sensitive data. While this paradigm ...
archive

The Impact of Work Values and Principal Job Attributes on Principal Selection Decisions.

Ask the publishers to restore access to 500,000+ books. An icon used to represent a menu that can be toggled by interacting with this icon. A line drawing of the Internet Archive headquarters building ...
Frontiers

LLM-based feature selection and counterfactual explanations applied to functional connectivity analysis in schizophrenia

1 School of Artificial Intelligence, Jiangsu Vocational College of Business, Nantong, China 2 School of Artificial Intelligence and Computer Science, Nantong University, Nantong, China Introduction: ...
Scientific Research Publishing

Parkinson’s Disease Diagnosis: Detecting the Effect of Attributes Selection and Discretization of Parkinson’s Disease Dataset on the Performance of Classifier Algorithms ()

Precise detection of PD is important in its early stages. Precise result can be achieved through data mining, classification techniques such as Naive Bayes, support vector machine (SVM), multilayer ...