An editor for Bayesian Networks built in React that uses Bayes' theorem.
What is a Bayesian network
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 anyone of several possible known causes was the contributing factor. For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms. Given symptoms, the network can be used to compute the probabilities of the presence of various diseases.
What is Bayes' Theorem
In probability theory and statistics, Bayes’ theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event. For example, if cancer is related to age, then, using Bayes’ theorem, a person's age can be used to more accurately assess the probability that they have cancer than can be done without the knowledge of the person’s age.
Bayes' Theorem is Mathematically stated as the following equation:
where A and B are events and P(B)!= 0
- P(A | B) is a conditional probability: the likelihood of event A occurring given that B is true.
- P(B | A) is also a conditional probability: the likelihood of event B occurring given that A is true.
- P(A) and P(B) are the probabilities of observing A and B independently of each other; this is known as the marginal probability.
git clone [email protected]:bayesjs/bayesjs-editor.git
cd bayesjs-editor
yarn // or npm install
To execute the unit test you can run:
yarn run test:unit
And to execute the integration test you can run when the project not running:
yarn run test:e2e
or, in case you wanna open the cypress while the project is running, in another terminal run:
yarn run cypress open
yarn start
MIT