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Statistical Agnostic Regression: a machine learning method to validate regression models
Regression analysis is a central topic in statistical modeling, aiming to estimate the relationships between a dependent variable, commonly referred to as the response variable, and one or more independent variables, i. e., explanatory variables.
Is K-fold cross validation the best model selection method for Machine Learning?
A novel statistical test based on K-fold CV and the Upper Bound of the actual error (K-fold CUBV) is composed, where uncertain predictions of machine learning with CV are bounded by the \emph{worst case} through the evaluation of concentration inequalities.
Tiled sparse coding in eigenspaces for the COVID-19 diagnosis in chest X-ray images
In this work, we propose a classification framework based on sparse coding in order to identify the pneumonia patterns associated with different pathologies.
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