Round 257

Round UUID: e5d18f01-7550-4bcf-9fda-56e6754a743e

Prompt:

Classify the entity as either Fylaran or Qtharri based on the following rules:

1. If mean_impact_crater_count >= 0.980:
   - If mean_surface_roughness >= 400 AND mean_core_density >= 0.93, classify as Fylaran
   - Otherwise, classify as Qtharri

2. If mean_impact_crater_count >= 0.965 and mean_impact_crater_count < 0.980:
   - If mean_surface_roughness < 200, classify as Qtharri
   - If mean_surface_roughness >= 400, classify as Fylaran
   - Otherwise, if mean_orbital_radius >= 2.85, classify as Fylaran
   - Otherwise, classify as Qtharri

3. If mean_impact_crater_count < 0.935, classify as Fylaran

4. If mean_impact_crater_count >= 0.945 and mean_impact_crater_count < 0.965:
   - If mean_surface_roughness < 100, classify as Qtharri
   - If mean_surface_roughness >= 450, classify as Qtharri
   - If mean_ring_system_complexity >= 0.965, classify as Qtharri
   - If mean_ring_system_complexity < 0.915, classify as Fylaran
   - If mean_ring_system_complexity >= 0.915 and mean_ring_system_complexity < 0.965:
     * If mean_surface_roughness >= 250 AND mean_surface_roughness < 450 AND mean_core_density < 0.93, classify as Fylaran
     * If mean_orbital_radius < 2.66, classify as Qtharri
     * If mean_orbital_radius >= 2.85, classify as Fylaran
     * Otherwise:
       - If mean_surface_roughness < 260, classify as Qtharri
       - If mean_core_density >= 0.915, classify as Qtharri
       - Otherwise, classify as Fylaran

5. If mean_impact_crater_count >= 0.935 and mean_impact_crater_count < 0.945:
   - If mean_ring_system_complexity < 0.90, classify as Fylaran
   - If mean_surface_roughness >= 350, classify as Fylaran
   - If mean_surface_roughness < 100, classify as Qtharri
   - Otherwise, classify as Qtharri

Apply these rules in order and stop at the first classification decision.

• Inferences: 569
• Created: 2025-08-02 12:21:23.298999+00:00
• First inference: 2025-08-02 12:21:44.277500+00:00
• Last inference: 2025-08-02 12:42:07.610107+00:00
• Completed: yes
• Train accuracy: 0.8318181818181818 (Krichevsky-Trofimov 0.080)
• Validation accuracy: 0.7777777777777778 (Krichevsky-Trofimov 0.109)
• Test accuracy: 0.8636363636363636 (Krichevsky-Trofimov 0.064)