Fig. 2: Comparison of different machine learning models to predict neutrophil percentage in PPMI and PDBP patients.
a–c Each model type was trained and tested on 100 train-test splits of 1254 samples with known neutrophil percentage, where samples were split 0.8–0.2 by participants. a plots the R2 value of each model when applied to the test sets, b plots the root mean squared errors, and c plots the mean absolute errors. A Wilcoxon signed-rank test was used to test the statistical significance of differences between the models for each metric. *, **, *** indicate p values less than 0.05, 0.01. and 0.001, while N.S. indicates no significance.
