meshcore-client

Commit Graph

Author	SHA1	Message	Date
zjs81	fffcff3b74	fix: cancel persist timer on dispose to prevent post-dispose writes	4 months ago
zjs81	b336aedbc5	fix: address PR #296 code review feedback - Clamp ML predictions between physics floor (raw airtime) and ceiling (worst-case formula) so model can never produce unsafe timeouts - Replace hourOfDay feature with secondsSinceLastRx for network activity - Remove unused _ContactStats.stdDev and dead model persistence code - Debounce observation writes (2s) instead of writing on every delivery - Skip recording observations when pathLength is null to avoid corrupting training data - Add comment explaining global (not per-contact) RX time tracking - Remove notifyListeners from retrain to avoid unnecessary widget rebuilds - Run dart format	4 months ago
zjs81	2ee2358ecc	feat: add ML-based adaptive timeout prediction using LinearRegressor Train a linear regression model on actual message delivery times to predict tighter timeouts, replacing worst-case physics estimates. Features: path length, message bytes, seconds since last RX, flood mode. Global model with per-contact blending after 10+ observations per contact. Falls back to existing physics formula when model has insufficient data.	4 months ago

Author

SHA1

Message

Date

zjs81

fffcff3b74

fix: cancel persist timer on dispose to prevent post-dispose writes

zjs81

b336aedbc5

fix: address PR #296 code review feedback

- Clamp ML predictions between physics floor (raw airtime) and ceiling
  (worst-case formula) so model can never produce unsafe timeouts
- Replace hourOfDay feature with secondsSinceLastRx for network activity
- Remove unused _ContactStats.stdDev and dead model persistence code
- Debounce observation writes (2s) instead of writing on every delivery
- Skip recording observations when pathLength is null to avoid corrupting
  training data
- Add comment explaining global (not per-contact) RX time tracking
- Remove notifyListeners from retrain to avoid unnecessary widget rebuilds
- Run dart format

zjs81

2ee2358ecc

feat: add ML-based adaptive timeout prediction using LinearRegressor

Train a linear regression model on actual message delivery times to
predict tighter timeouts, replacing worst-case physics estimates.
Features: path length, message bytes, seconds since last RX, flood mode.
Global model with per-contact blending after 10+ observations per contact.
Falls back to existing physics formula when model has insufficient data.

3 Commits (integration/290-306-335)