## Line Chart: Model Accuracy vs Number of Operands (digits=2) for Different Recurrence Levels ### Overview The chart visualizes the relationship between model accuracy and the number of operands (2–6) across nine recurrence levels (1, 2, 4, 8, 16, 24, 32, 48, 64). Accuracy is plotted on the y-axis (0–1.0), while the x-axis represents the number of operands. Each recurrence level is represented by a distinct colored line, with trends showing how accuracy changes as operands increase. --- ### Components/Axes - **Title**: "Model Accuracy vs Number of Operands (digits=2) for Different Recurrence Levels" - **X-axis**: "Number of Operands" (values: 2, 3, 4, 5, 6) - **Y-axis**: "Accuracy" (scale: 0.0 to 1.0) - **Legend**: Located on the right, mapping recurrence levels to colors: - Recurrence 1: Blue - Recurrence 2: Orange - Recurrence 4: Green - Recurrence 8: Red - Recurrence 16: Purple - Recurrence 24: Brown - Recurrence 32: Pink - Recurrence 48: Gray - Recurrence 64: Yellow --- ### Detailed Analysis 1. **Recurrence 1 (Blue)**: - Starts at **0.95** (operands=2), drops to **0.15** (operands=3), then **0.05** (operands=4), rises to **0.45** (operands=5), and falls to **0.25** (operands=6). 2. **Recurrence 2 (Orange)**: - Flat line at **0.0** for all operands. 3. **Recurrence 4 (Green)**: - Flat line at **0.0** for all operands. 4. **Recurrence 8 (Red)**: - Starts at **0.7** (operands=2), drops to **0.05** (operands=3), then **0.0** (operands=4), rises to **0.05** (operands=5), and falls to **0.0** (operands=6). 5. **Recurrence 16 (Purple)**: - Starts at **0.9** (operands=2), drops to **0.5** (operands=3), then **0.2** (operands=4), rises to **0.4** (operands=5), and falls to **0.2** (operands=6). 6. **Recurrence 24 (Brown)**: - Starts at **0.85** (operands=2), drops to **0.5** (operands=3), then **0.1** (operands=4), rises to **0.5** (operands=5), and falls to **0.15** (operands=6). 7. **Recurrence 32 (Pink)**: - Starts at **0.95** (operands=2), drops to **0.35** (operands=3), then **0.1** (operands=4), rises to **0.55** (operands=5), and falls to **0.1** (operands=6). 8. **Recurrence 48 (Gray)**: - Starts at **0.85** (operands=2), drops to **0.5** (operands=3), then **0.05** (operands=4), rises to **0.4** (operands=5), and falls to **0.15** (operands=6). 9. **Recurrence 64 (Yellow)**: - Starts at **1.0** (operands=2), drops to **0.5** (operands=3), then **0.1** (operands=4), rises to **0.45** (operands=5), and falls to **0.15** (operands=6). --- ### Key Observations - **High Recurrence Levels (32, 48, 64)**: Show sharp initial drops in accuracy as operands increase from 2 to 3, followed by partial recovery at operands=5. Recurrence 64 has the highest initial accuracy (1.0) but the steepest decline. - **Low Recurrence Levels (1, 2, 4, 8)**: Recurrence 2 and 4 have no accuracy (flat at 0.0). Recurrence 8 and 1 show minimal recovery after operand=3. - **Recurrence 16 and 24**: Demonstrate moderate recovery at operand=5 but fail to maintain high accuracy across all operands. - **Recurrence 32**: Exhibits the most pronounced recovery at operand=5 (0.55) but collapses at operand=6. --- ### Interpretation The data suggests a trade-off between recurrence level and model robustness. Higher recurrence levels (e.g., 64) achieve near-perfect accuracy at operand=2 but degrade rapidly with increasing complexity. Lower recurrence levels (e.g., 1, 16) show more gradual declines but lack the initial precision of higher levels. Recurrence 32 stands out for its mid-range performance, balancing initial accuracy with partial recovery at operand=5. The flat lines for Recurrence 2 and 4 indicate these configurations fail to capture any meaningful patterns, possibly due to insufficient model capacity or data representation. This highlights the importance of tuning recurrence levels based on operand complexity and task requirements.