Round 128

Round UUID: f267cfff-d153-4188-9e8c-a2167e5c239f

Prompt:

Predict the classification based on the following rules. Use the first rule that matches:

1. If mean_atmospheric_depth >= 6.7 AND mean_surface_roughness >= 200, predict Fylaran.
2. Else if max_atmospheric_depth >= 7.0 AND mean_surface_roughness >= 100, predict Fylaran.
3. Else if max_atmospheric_depth >= 6.8 AND mean_surface_roughness >= 100, predict Fylaran.
4. Else if mean_atmospheric_depth >= 6.2 AND mean_surface_roughness >= 350 AND max_atmospheric_depth >= 6.8, predict Fylaran.
5. Else if mean_cloud_turbulence >= 480 AND mean_axial_symmetry >= 480 AND mean_atmospheric_depth >= 6.0 AND max_atmospheric_depth >= 6.5, predict Fylaran.
6. Else if mean_surface_roughness >= 500 AND mean_atmospheric_depth >= 6.5, predict Fylaran.
7. Else if mean_axial_symmetry >= 500 AND mean_cloud_turbulence >= 450 AND mean_atmospheric_depth >= 6.2, predict Fylaran.
8. Else if mean_surface_roughness >= 400 AND mean_cloud_turbulence >= 470 AND mean_atmospheric_depth < 6.0, predict Fylaran.
9. Else if mean_core_density >= 0.92 AND mean_atmospheric_depth < 6.2, predict Qtharri.
10. Else (if none of the above conditions is met), predict Qtharri.

Classification:

• Inferences: 569
• Created: 2025-03-31 16:01:38+00:00
• First inference: 2025-03-31 16:01:41+00:00
• Last inference: 2025-03-31 16:53:31+00:00
• Completed: yes
• Train accuracy: 0.9 (KT 0.046)
• Validation accuracy: 0.8253968253968254 (KT 0.084)
• Test accuracy: 0.9090909090909091 (KT 0.042)