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Fig. 2 | BMC Bioinformatics

Fig. 2

From: Harvestman: a framework for hierarchical feature learning and selection from whole genome sequencing data

Fig. 2

The knowledge graph is more informative than raw SNPs. AUC as a function of feature counts for five year survival (top) and five year disease free survival (bottom) obtained with logistic regression (left), random forest (middle), and SVM (right). Each point in each figure corresponds to a knowledge graph that has been filtered by one of four MI thresholds (0.125, 0.1, 0.075, and 0.05.). The points are ordered from left to right in order of decreasing MI thresholds. Harvestman selects different numbers of features (x-axis), depending on the input graph. Comparisons are made using models trained on binary encodings of SNPs that passed those same thresholds. This figure was generated using Matplotlib version 3.2.1

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BMC Bioinformatics

ISSN: 1471-2105

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