Julian Pawlowski 7ee013daf2 feat(outliers): adaptive confidence based on daily volatility ... Outlier smoothing now adapts to daily price volatility (CV): - Flat days (CV≤10%): conservative (confidence=2.5), fewer false positives - Volatile days (CV≥30%): aggressive (confidence=1.5), catch more spikes - Linear interpolation between thresholds Uses calculate_coefficient_of_variation() for consistency with volatility sensors. Impact: Better outlier detection that respects natural price variation patterns. Flat days preserve more structure, volatile days get stronger smoothing.		2025-12-22 23:21:44 +00:00
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tibber_prices	feat(outliers): adaptive confidence based on daily volatility	2025-12-22 23:21:44 +00:00