Browsing Research Output by Subject "Variable selection"
Now showing items 1-3 of 3
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Metabolomics variable selection and classification in the presence of observations below the detection limit using an extension of ERp
(BioMed Central, 2017)Background ERp is a variable selection and classification method for metabolomics data. ERp uses minimized classification error rates, based on data from a control and experimental group, to test the null hypothesis of ... -
Variable importance in latent variable regression models
(Wiley, 2014)The quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable ... -
Variable selection for binary classification using error rate p-values applied to metabolomics data
(BioMed Central, 2016)Background: Metabolomics datasets are often high-dimensional though only a limited number of variables are expected to be informative given a specific research question. The important task of selecting informative variables ...