We demonstrate a concept and implementation of a compendium for the classification of high-dimensional data from …

between two classes of samples, for example between tumour types. Users are confronted with a multitude of classification … compare important characteristics of a range of classification methods, including simple univariate filtering, penalised … likelihood methods and the random forest.Classification accuracy is an important characteristic, but the biological …

wrapper method starts from any classification algorithm and weights each variable (i.e. gene) relative to its efficiency for … classification. An optimization procedure is then inferred which exhibits important genes for the studied biological process. Theory … and application with the SVM classifier were presented in Gadat and Younes, 2007 and we extend this method with CART. The …

metabolomics studies. As a classification method, Principal Component Discriminant Analysis is used; however, the methodology can … biomarkers are identified using the variable selection method. In each cross-validation loop a classification model is built. The … final classification uses a majority voting scheme from the ensemble classifier. …

This note is a comment on the article "Dimension Reduction for Classification with Gene Expression Microarray Data …

This paper gives a description of the structure of the classification competition on mass spectrometry proteomic data …