CarsonScott/Online-Relationship-Learning
Unsupervised ML algorithm for predictive modeling and time-series analysis
This project helps systems engineers and operations managers predict events and adapt to changing input patterns in real-time. It takes a stream of event data or sensor readings as input and identifies the relationships between these inputs over time. The output is a self-adjusting prediction model that anticipates future events or system states, improving its accuracy as more data is observed.
No commits in the last 6 months.
Use this if you need to build a system that can learn and predict sequences of events or states based on real-time data without explicit programming of rules.
Not ideal if you require explainable predictions with human-readable rules or if your data does not exhibit temporal relationships between events.
Stars
40
Forks
5
Language
Python
License
—
Category
Last pushed
Sep 30, 2020
Commits (30d)
0
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