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Fig. 2 | BMC Bioinformatics

Fig. 2

From: Classification based on extensions of LS-PLS using logistic regression: application to clinical and multiple genomic data

Fig. 2

Mean misclassification rates from the central nervous system (CNS) data set using the six methods considering different numbers of selected genes pred: 50, 100, 500 and 750. GLM and R-PLS denote the misclassification rates and AUCs obtained from applying the GLM to the clinical data alone and PLS to the gene expression data alone, respectively. LS-PCR denotes the approach derived from PCR, where gene expression data are analyzed using PCA and IRLS can thus be applied to the merged data set of PCA scores and clinical data. LS-PLS-IRLS, R-LS-PLS, and IR-LS-PLS denote the misclassification rates obtained from the newly proposed LS-PLS approaches combining expression and clinical data. For each method, a line is drawn to connect symbols to improve readability

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