The Tornado 🌪️ framework, designed and implemented for adaptive online learning and data stream mining in Python.
Algorithms for detecting changes from a data stream.
An approach to apply concept drifts and ADWIN on the streams event time to reason about the progress of watermarks
Code for testing Concept drift techniques on a real word dataset on a hexapod robot
This project implements an AutoML-driven adaptive drift detection framework for COVID-19 forecasting, leveraging ADWIN & DDM to dynamically adjust models in response to concept drift. It enhances predictive accuracy by intelligently retraining models, ensuring robust time-series forecasting under evolving data conditions.
Салон штор
Streaming, drift-aware log anomaly detection with conformal calibration; reproducible, CI-tested Python and strict provenance.
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