Machine learning algorithm validation with a limited sample size

Advances in neuroimaging, genomic, motion tracking, eye-tracking and many other technology-based data collection methods have led to a torrent of high dimensional datasets, which commonly have a small number of samples because of the intrinsic high cost of data collection involving human participant...

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Veröffentlicht in:	PloS one Jg. 14; H. 11; S. e0224365
Hauptverfasser:	Vabalas, Andrius, Gowen, Emma, Poliakoff, Ellen, Casson, Alexander J.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 07.11.2019 Public Library of Science (PLoS)
Schlagworte:	Accuracy Algorithms Artificial intelligence Autism Bias Bioinformatics Biological markers Biology and Life Sciences Biomarkers Biomedical Research - statistics & numerical data Brain research Classification Computer and Information Sciences Computer simulation Data analysis Data collection Data Interpretation, Statistical Data mining Datasets Diagnostic imaging Estimates Humans Internet of Things Learning algorithms Machine Learning Medical imaging Medicine and Health Sciences Methods Neuroimaging Neurology Noise Normal distribution Parameters Pattern recognition Physical Sciences Research and Analysis Methods Sample Size Social Sciences Spectrum analysis Studies Technology Test procedures Tracking United Kingdom > UK England
ISSN:	1932-6203, 1932-6203
Online-Zugang:	Volltext
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