On effectively predicting autism spectrum disorder therapy using an ensemble of classifiers
Abstract An ensemble of classifiers combines several single classifiers to deliver a final prediction or classification decision. An increasingly provoking question is whether such an ensemble can outperform the single best classifier. If so, what form of ensemble learning system (also known as mult...
Main Authors: | Bhekisipho Twala, Eamon Molloy |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-11-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-46379-3 |
Similar Items
-
Voice acoustics allow classifying autism spectrum disorder with high accuracy
by: Frédéric Briend, et al.
Published: (2023-07-01) -
Employing Machine Learning-Based Predictive Analytical Approaches to Classify Autism Spectrum Disorder Types
by: Muhammad Kashif Hanif, et al.
Published: (2022-01-01) -
Multi-classifier fusion based on belief-value for the diagnosis of autism spectrum disorder
by: Feng Zhao, et al.
Published: (2023-11-01) -
Modified Meta Heuristic BAT with ML Classifiers for Detection of Autism Spectrum Disorder
by: Mohemmed Sha, et al.
Published: (2023-12-01) -
Use of Complementary and Alternative Therapies in Autism Spectrum Disorder
by: Zehra Hangül, et al.
Published: (2022-06-01)