Fig. 3: Classification performance.
From: Hierarchical progressive learning of cell identities in single-cell data
a–c Boxplots showing the HF1-score of the one-class and linear SVM during n-fold cross-validation on the a simulated (n = 10), b PBMC-FACS (n = 10), and c AMB (n = 5) dataset. In the boxplots, the middle (orange) line represents the median, the lower and upper hinge represents the first and third quartiles, and the lower and upper whiskers represent the values no further than 1.5 interquartile range away from the lower and upper hinge, respectively. d Barplot showing the percentage of true positives (TP), false negatives (FN), and false positives (FP) per classifier on the AMB dataset. For the TPs a distinction is made between correctly predicted leaf nodes and internal nodes. e Heatmap showing the percentage of unlabeled cells per classifier during the different rejection experiments. f Heatmap showing the F1-score per classifier per cell population on the AMB dataset. Gray indicates that a classifier never predicted a cell to be of that population.
