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feat: Implement Smart Adaptive Prediction using K-Means and Hysteresis #49

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feat: Implement Smart Adaptive Prediction using K-Means and Hysteresis #49

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@whitestorm007 whitestorm007 commented Jan 1, 2026

I've upgraded the core detection engine to solve the static threshold limitations mentioned in the original research.

Key Improvements:

  • Dynamic Clustering: Implemented K-Means to automatically learn the network's specific "Online" vs "Standby" RTT profiles.
  • Noise Filtering: Added Interquartile Range (IQR) analysis to filter out random network jitter/spikes.
  • Stability: Introduced a Hysteresis loop (3-strike rule) to eliminate state flickering.
  • UX: Updated dashboard to visualize confidence levels and cluster separation.

@whitestorm007 whitestorm007 force-pushed the feat/adaptive-thresholds branch from a034f3a to a006fc7 Compare January 1, 2026 11:17
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