RFE and the learning curve for the SVM model are depicted in (A) and (B), respectively.

<p>The best performance is achieved with a total of 310 characteristics, as shown by (A). In (B), the learning curve is presented for the training Accuracy (blue) and test Accuracy (green) using the entire dataset (600 connectivity matrices subjects). The highest performance was achieved with...

Full description

Saved in:

Bibliographic Details
Main Author:	Caroline L. Alves (14271413) (author)
Other Authors:	Tiago Martinelli (10402035) (author), Loriz Francisco Sallum (19865127) (author), Francisco Aparecido Rodrigues (19865130) (author), Thaise G. L. de O. Toutain (19865133) (author), Joel Augusto Moura Porto (19865136) (author), Christiane Thielemann (14271419) (author), Patrícia Maria de Carvalho Aguiar (19865139) (author), Michael Moeckel (19865142) (author)
Published:	2024
Subjects:	Medicine Cell Biology Neuroscience Biotechnology Science Policy Mental Health Biological Sciences not elsewhere classified totaling 120 subjects targeted intervention difficult surpassing existing benchmarks observed connectivity patterns brain network integration autism spectrum disorder achieve superior accuracy brain regions critical leveraging multiclass classification asd show disruptions ml classification rests multiclass classification regions involved typically developed three groups segregation among promising avenue overlapping symptoms impulse control findings pave established practices enhanced diagnostics cognitive functions clinical symptoms accurate diagnosis
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

RFE and the learning curve for the SVM model are depicted in (A) and (B), respectively.

Similar Items