Cargando…
A topological classifier to characterize brain states: When shape matters more than variance
Despite the remarkable accuracies attained by machine learning classifiers to separate complex datasets in a supervised fashion, most of their operation falls short to provide an informed intuition about the structure of data, and, what is more important, about the phenomena being characterized by t...
Autores principales: | Ferrà, Aina, Cecchini, Gloria, Nobbe Fisas, Fritz-Pere, Casacuberta, Carles, Cos, Ignasi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10545107/ https://www.ncbi.nlm.nih.gov/pubmed/37782651 http://dx.doi.org/10.1371/journal.pone.0292049 |
Ejemplares similares
-
Algebraic Topology : New Trends in Localization and Periodicity : Barcelona Conference
por: Broto, Carles, et al.
Publicado: (1996) -
Conference on Algebraic Topology : A Euroconference on Advances in Homotopy Theory
por: Aguadé, Jaume, et al.
Publicado: (2001) -
Analysis of variance (ANOVA) comparing means of more than two groups
por: Kim, Hae-Young
Publicado: (2014) -
When shapes are more than shapes: perceptual, developmental, and neurophysiological basis for attributions of animacy and theory of mind
por: Torabian, Sajjad, et al.
Publicado: (2023) -
The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets
por: Saito, Takaya, et al.
Publicado: (2015)