Supplementary Figure 3: Calibration of the sequential SVM classifier SplashRNA. | Nature Biotechnology

Supplementary Figure 3: Calibration of the sequential SVM classifier SplashRNA.

From: Prediction of potent shRNAs with a sequential classification algorithm

Supplementary Figure 3

(a) Precision-recall trade-off between the two classifiers SplashmiR-30 and SplashmiR-E. Selection of alpha (α) and theta (θ) hyperparameters leads to varied performance (area under the precision-recall curve, auPR) on the TILE miR-30 (x-axis) and miR-E + UltramiR (y-axis) sets. Each line represents a setting of alpha; points on the line represent distinct theta values. The circle indicates the alpha and theta choices for the final sequential classifier (SplashRNA: α = 0.6, θ = 1.1). The dashed line represents the performance of the convex linear classifier without a threshold at every alpha. Note that the performance of a sequential classifier equals or exceeds that of a linear combination since one can set the threshold (θ) to a small enough value such that all examples are evaluated by both classifiers.

(b) Performance on the TILE set, varying the value for theta with alpha set to 0.6. The insert shows a zoom in of the first 15% of the precision-recall.

(c) Performance on the miR-E + UltramiR set, varying the value for theta with alpha set to 0.6.

Back to article page