Fig. 5
From: Using ensemble learning for classifying artistic styles in traditional Chinese woodcuts
Performance Comparison of Proposed Ensemble Method against Baseline Models. Subplots (a), (b), and (c) illustrate the stability and consistency of Precision, Recall, and F-Measure, respectively, for each model across 10 cross-validation folds. Subplot (d) presents the overall average performance metrics (Precision, Recall, and F-Measure) for all compared models, providing a consolidated view of their classification quality.
