Model Dashboard
Portfolio Models Overview
Live command center for all active models. Tracking the latest machine learning forecasts, signal strength, and prediction horizons across your targets.
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Run the training pipeline (Phase 40) to generate your first models.
Forecast
Position
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Phase 40 • Training
Model Story
A story-driven view of each run: trust (performance), drivers (what mattered), adaptation (how it shifts in stress), and blind spots (when it fails).
Select a target and a run to load the model story.
Reliability (Calibration)
Verification: Does "60% probability" actually mean 60% win rate? Points should hug the diagonal line.
Reality Check
Select a run to compute backtest performance…
Prediction Confidence
Select a run to compute prediction uncertainty…
Evolution of Trust
Track how allocation rotates across base models over time (stacked to 100%), with the target-specific benchmark overlaid to reveal who is driving decisions in each regime. Represents the StackedEnsemble model.
Signal Forensics
Compare the stacked ensemble (blue) against the actual target (black) and the underlying base models (dotted).
Model Stability (Rolling Log Loss)
Consistency check: Spikes indicate regime failures where the model stopped understanding the market.
Voting Ensemble
Blind Spots
Select a run to analyze error patterns (e.g., error vs volatility) and identify failure modes…
Comparison
Compare candidate models against the Conservative (Voting) ensemble. Blue indicates the Champion. Green indicates the Voting System.
The Brain
The final feature set used by this run, grouped by type (Volatility / Momentum / Macro / Other).
Numbers represent feature importance scores (relative contribution to prediction).
Drivers
Ranked importance across the base model layer (normalized). Shows what drove predictions most.
Phase 50 • Signal
Signal Dashboard
See what the model predicts next and why. This view reads the latest Phase 50 artifacts and explains the signal strength using the same thresholds the system uses internally.
Pick a target and (optionally) a snapshot.
The Speedometer
A live read of the current signal for the selected target, expressed as probability or forecast value.
Ensemble Composition
Select a target to reveal how this signal was generated.
The Forecast Uncertainty range spans from Low to High (90% confidence). The inner colored band highlights the spread between the Aggressive and Conservative strategies.
The prediction range crosses 0%, indicating the model sees potential for both loss and gain.
How Much to Trust This Signal
A risk-aware view of today’s forecast. The band summarizes uncertainty (model disagreement or historical error).
This forecast lacks historical error data.
dashboard_snapshot.json from the training run to display these bands.
Range of predictions from individual base models (Level 0).
Why the Model Thinks This
Feature contributions for this specific prediction. Positive bars push the forecast up; negative bars push it down.
No embedded explanation was found for this target yet. Phase 50 must persist explanation details inside latest_forecasts.json.