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As a technique that can compactly represent complex patterns, machine learning has significant potential for predictive inference. K-fold cross-validation (CV) is the most common approach to ascertaining the likelihood that a machine learning outcome
Externí odkaz:
http://arxiv.org/abs/2401.16407
Publikováno v:
In International Journal of Applied Earth Observation and Geoinformation November 2024 134
Publikováno v:
Volume 510, 21 October 2022, Pages 159-171
There remains an open question about the usefulness and the interpretation of Machine learning (MLE) approaches for discrimination of spatial patterns of brain images between samples or activation states. In the last few decades, these approaches hav
Externí odkaz:
http://arxiv.org/abs/2202.04397
Autor:
Macías, José A, Borges, Clemente R.
Publikováno v:
In Science of Computer Programming May 2024 234
Publikováno v:
In International Journal of Applied Earth Observation and Geoinformation March 2024 127
Autor:
Vázquez-Marrufo, M., Sarrias-Arrabal, E., García-Torres, M., Martín-Clemente, R., Izquierdo, G.
Publikováno v:
In Neurología (English Edition) October 2023 38(8):577-590
Autor:
Vázquez-Marrufo, M., Sarrias-Arrabal, E., García-Torres, M., Martín-Clemente, R., Izquierdo, G.
Publikováno v:
In Neurología October 2023 38(8):577-590
Autor:
Poblete, T., Navas-Cortes, J.A., Hornero, A., Camino, C., Calderon, R., Hernandez-Clemente, R., Landa, B.B., Zarco-Tejada, P.J.
Publikováno v:
In Remote Sensing of Environment 1 September 2023 295
Publikováno v:
In Soil & Environmental Health June 2023 1(2)
Autor:
Belwalkar, A., Poblete, T., Longmire, A., Hornero, A., Hernandez-Clemente, R., Zarco-Tejada, P.J.
Publikováno v:
In Remote Sensing of Environment May 2022 273