Generalized additive model for location, scale and shape
The Generalized Additive Model for Location, Scale and Shape (GAMLSS) is an approach to statistical modelling and learning. GAMLSS is a modern distribution-based approach to (semiparametric) regression. A parametric distribution is assumed for the response (target) variable but the parameters of this distribution can vary according to explanatory variables using linear, nonlinear or smooth functions. In machine learning parlance, GAMLSS is a form of supervised machine learning.
Generalized additive model for location, scale and shape
The Generalized Additive Model for Location, Scale and Shape (GAMLSS) is an approach to statistical modelling and learning. GAMLSS is a modern distribution-based approach to (semiparametric) regression. A parametric distribution is assumed for the response (target) variable but the parameters of this distribution can vary according to explanatory variables using linear, nonlinear or smooth functions. In machine learning parlance, GAMLSS is a form of supervised machine learning.
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In der Statistik sind verallge ...... n Variablen modelliert werden.
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The Generalized Additive Model ...... ions of explanatory variables.
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December 2019
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In der Statistik sind verallge ...... ungsmodelle an die Daten. Das
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The Generalized Additive Model ...... f supervised machine learning.
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Generalized additive model for location, scale and shape
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Verallgemeinerte additive Modelle für Lage-, Skalen- und Formparameter
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