Skip to main content
Fig. 2 | BMC Bioinformatics

Fig. 2

From: Randomized boosting with multivariable base-learners for high-dimensional variable selection and prediction

Fig. 2

High-dimensional illustrative data example. Coefficient paths \(\beta _j^{[t]}\) for \(j\in {{\mathcal {P}}}\) along the number of iterations t of \(L_2\)Boosting, RSubBoost and AdaSubBoost. Horizontal black dotted lines indicate the component values of the true \(\varvec{\beta }\). For \(L_2\)Boosting, the vertical red line indicates the CV-optimal stopping iteration \(m_{{\text {CV}}}\), while for RSubBoost and AdaSubBoost the automatic stopping after the first \(N_{{{\text {stop}}}}=p/2=500\) succeeding iterations without any updates is indicated

Back to article page

BMC Bioinformatics

ISSN: 1471-2105

Contact us