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Figure 9 | BMC Bioinformatics

Figure 9

From: Analysis of nanopore detector measurements using Machine-Learning methods, with application to single-molecule kinetic analysis

Figure 9

AdaBoosting to select 100 from the full set of 2600 features improves classification over just passing all 2600 components to the SVM. However, the best performance is still obtained when working with the Adaboosting from the manual set. (The Y-axis, "SN + SP", shows the sum of the Sensitivity and the Specificity. The X-axis is the kernel parameter σ.)

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