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Error estimation in pattern recognition

The main training objective of the learning object is to introduce some of the most popular estimators for classification error: resubstitution, holdout, K-fold cross validation, bootstrap and repeated variants for holdout and K-fold cross validation. They are described at a basic level and then compared in terms of bias and variability. Juan Císcar, A.; Sanchis Navarro, JA.; Civera Saiz, J. (2019). Error estimation in pattern recognition. http://hdl.handle.net/10251/121299 DER

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