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A connection between the pattern classification problem and the General Linear Model for statistical inference
A connection between the General Linear Model (GLM) in combination with classical statistical inference and the machine learning (MLE)-based inference is described in this paper.
Statistical Agnostic Mapping: a Framework in Neuroimaging based on Concentration Inequalities
In the 70s a novel branch of statistics emerged focusing its effort in selecting a function in the pattern recognition problem, which fulfils a definite relationship between the quality of the approximation and its complexity.
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