A Bayesian network is a probabilistic graphical model (a type of statistical model) that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). Bayesian networks are ideal for taking an event that occurred and predicting the likelihood that any one of several possible known causes was the contributing factor.
More details in Wikipedia.
Our plugin gets flows of information from one or more inputs and can perform a probabilistic inference through several steps:
- Read a Bayesian network definition from a .json file;
- Set a data source which stores data flows;
- Associate flows to network's nodes;
- Perform probabilistic inference;
- Write results in a database. In our case InfluxDB is the default one;
- Display the results with Grafana default panel (Graph, Singlestat, etc);
npm install
npm run build
We are Computer Science students at University of Padua. The plugin has been developed for Software Engineering course.
7DOS is composed of seven members:
- Andrea Trevisin
- Giacomo Barzon
- Giovanni Sorice
- Lorenzo Busin
- Marco Costantino
- Michele Roverato
- Nicolò Tartaggia
The project documents are here (only available in Italian).