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. Author manuscript; available in PMC: 2018 Jun 3.
Published in final edited form as: Adv Neural Inf Process Syst. 2016 Dec;29:3567–3575.

Table 2.

Labeling function (LF) summary statistics, sizes of generated training sets Sλ≠0 (only counting non-zero labels), and relative F1 score improvement over baseline IRT methods for hand-tuned (HT) and LSTM-generated (LSTM) feature sets.

Application # of LFs Coverage |Sλ≠0| Overlap Conflict F1 Score Improvement
HT LSTM
KBP (News) 40 29.39 2.03M 1.38 0.15 1.92 3.12
Genomics 146 53.61 256K 26.71 2.05 1.59 0.47
Pharmacogenomics 7 7.70 129K 0.35 0.32 3.60 4.94
Diseases 12 53.32 418K 31.81 0.98 N/A N/A