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Maddrey's discriminant function (DF) is the traditional model for evaluating the severity and prognosis in alcoholic hepatitis and evaluates the efficacy of using alcoholic hepatitis steroid treatment. The Maddrey DF score is a predictive statistical model compares the subject's DF score with mortality prognosis within 30-day or 90-day scores.
MDCalc is a free online medical reference for healthcare professionals that provides point-of-care clinical decision-support tools, including medical calculators, scoring systems, and algorithms. [1] MDCalc is also a mobile and web app. [ 2 ] The decision-support tools are based on published clinical research, [ 3 ] and MDCalc’s content is ...
Linear discriminant analysis (LDA), normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics and other fields, to find a linear combination of features that characterizes or separates two or more classes of objects or events.
Optimal Discriminant Analysis (ODA) [1] and the related classification tree analysis (CTA) are exact statistical methods that maximize predictive accuracy. For any specific sample and exploratory or confirmatory hypothesis, optimal discriminant analysis (ODA) identifies the statistical model that yields maximum predictive accuracy, assesses the ...
One popular example of an algorithm that assumes homoscedasticity is Fisher's linear discriminant analysis. The concept of homoscedasticity can be applied to distributions on spheres. The concept of homoscedasticity can be applied to distributions on spheres.
In mathematics, the discriminant of a polynomial is a quantity that depends on the coefficients and allows deducing some properties of the roots without computing them. More precisely, it is a polynomial function of the coefficients of the original polynomial. The discriminant is widely used in polynomial factoring, number theory, and algebraic ...
The average variance extracted has often been used to assess discriminant validity based on the following "rule of thumb": the positive square root of the AVE for each of the latent variables should be higher than the highest correlation with any other latent variable. If that is the case, discriminant validity is established at the construct ...
In statistics, kernel Fisher discriminant analysis (KFD), [1] also known as generalized discriminant analysis [2] and kernel discriminant analysis, [3] is a kernelized version of linear discriminant analysis (LDA). It is named after Ronald Fisher.