Fig. 2From: Machine learning approach for Migraine Aura Complexity Score prediction based on magnetic resonance imaging dataPredicted vs. real average MACS for SVM algorithm and correlation-based feature selection (p < 0.05). The x-axis shows predicted average MACS and the y-axis real average MACS scores. The prediction is performed using the SVM algorithm and features that correlate with average MACS with a 0.05 significance level. Each black dot represents one subject. This model achieved R2 = 0.47, MAE = 1.449, and RMSE = 1.8309Back to article page