Once a team completes all three missions, the activity enters its final and most pedagogically rich phase. Instead of writing more code, students are now asked to act as data scientists who must justify a model choice to a stakeholder audience. This phase has two parts: a comparator that surfaces the tracked metrics and artifacts for all three runs side by side, and a defense submission that requires students to document their reasoning in a structured, evidence-grounded form. Completing the defense seals the team’s record and awards the final +25 points.Documentation Index
Fetch the complete documentation index at: https://mintlify.com/elenacarino-max/Pildora4_ext_StarWars/llms.txt
Use this file to discover all available pages before exploring further.
The comparator
The comparator view presents all three mission runs — Mision_Tatooine, Mision_Coruscant, and Mision_Mustafar — alongside each other so teams can identify differences and trends before committing to a recommendation. For each run the comparator shows: Tracked metrics:| Metric | Description |
|---|---|
accuracy | Overall fraction of correctly classified digits |
precision_weighted | Class-weighted precision across all 10 digits |
recall_weighted | Class-weighted recall across all 10 digits |
f1_weighted | Harmonic mean of precision and recall, class-weighted |
recall_1 | Recall specifically for digit 1 (fraction of true 1s correctly identified) |
recall_8 | Recall specifically for digit 8 (fraction of true 8s correctly identified) |
matriz_confusion.png— a visual confusion matrix showing per-class prediction patternsclassification_report.json— the full per-class precision, recall, and F1 breakdown as structured JSON
Orden 66 — Receiving the holocron
After the comparator, each team presses the Orden 66 button to reveal their unique holocron challenge card. Holocrons are assigned deterministically based on team join order within the session, cycling through all seven challenges so that different teams in the same classroom receive different analytical lenses. The instructor can reassign a holocron from the admin panel if needed. The holocron card states a specific task and a series of investigation steps that frame how the team should approach their defense. All seven challenges require evidence from the tracked runs, but each emphasises a different concern — from audit reproducibility to non-technical communication to per-class recall analysis.The seven holocron challenges
◈ Consejo desconfiado
Focus: evidencias — Convence a un Consejo que no acepta una recomendación basada únicamente en accuracy. Requiere al menos dos métricas, un artefacto y una limitación explícita.
◒ Recursos limitados
Focus: complejidad — Decide si la mejora de Mustafar (300 árboles) compensa su mayor coste frente a runs con 50 ó 100 árboles. Evalúa rendimiento frente a número de estimadores.
⌁ Auditoría imperial
Focus: trazabilidad — Prepara una auditoría que permita a otro equipo identificar los cinco parámetros, cuatro métricas, dos artefactos y el modelo registrado, y que indique qué faltaría para reproducción perfecta.
◎ Senado galáctico
Focus: comunicación — Presenta la decisión al Senado sin jerga técnica. Traduce la métrica principal a lenguaje llano y usa la matriz de confusión para ilustrar un error concreto.
◐ El lado oscuro de la métrica
Focus: recall_8 — Investiga si una accuracy alta oculta fallos en el dígito 8. Compara
recall_8 entre las tres runs y localiza en la matriz con qué otros dígitos se confunde el 8.✦ Rescate prioritario
Focus: recall_1 — El rescate depende de detectar tantos dígitos 1 reales como sea posible. Prioriza
recall_1 incluso si ello implica sacrificar accuracy global; justifica el riesgo aceptado.⬡ Misión en producción
Focus: producción — Decide qué run está lista para producción. Combina rendimiento, coste (número de árboles), trazabilidad (parámetros y modelo registrado) y propone un control adicional antes del despliegue.
Submitting the defense
The defense form has seven required fields. Every field must be filled before the team can seal the defense; leaving any field blank will show a validation error. Once sealed, the defense is stored permanently against the team record and the +25 points are applied.selected_run
The name of the run the team recommends (one of
Mision_Tatooine, Mision_Coruscant, or Mision_Mustafar). This must be different from discarded_run.evidence
The metric or metrics used to justify the selection — e.g. “Mustafar tiene el mayor f1_weighted (0.9692) y recall_1 (1.0)”. Teams should refer to specific numeric values from the comparator.
artifact
The artifact consulted during the analysis — either
matriz_confusion.png or classification_report.json. Teams should note what specific information the artifact revealed.discard_reason
An evidence-based explanation of why the discarded run was not chosen — e.g. “Tatooine tiene recall_1=0.9167, significativamente inferior a Mustafar”.
limitation
One honest acknowledged limitation of the chosen model or decision — e.g. “recall_8 permanece en 0.8571 en las tres runs; el modelo no mejora para el dígito 8 independientemente del número de árboles”.
The
selected_run and discarded_run fields must contain different run names. If both are set to the same value, the form will reject the submission with the message “La run elegida y la descartada deben ser distintas.”