Linear SVM (C=inf) vs. RBF-kernel SVM (C=inf, gamma=auto) over 10 bootstrap samples.
Linear SVM trained using SVMlight, using C=infinity.
RBF-kernel SVM trained using SVMlight, using C=infinity, selecting best gamma in [?].
Tested on out-of-sample examples for each bootstrap.
Negatives: N2 (Direct annotations to any ancestor node are not used as negatives).

AUCs: Mean ± StDev of Area under ROC Curve over 10 bootstrap samples.
C.Median: AUC of Bagging classifier, aggregating predictions by median (voting).
(Each Bagging weak classifier only contributes test output on examples held-out from it.)
Pos: Number of positive examples available.
Recall ≥ 10%: Best precision over recalls ≥0.10 and its highest corresponding recall.
TP ≥ 10%: Best precision over recalls ≥(10/Pos) and its highest corresponding recall.

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