Similarly to the classification extension, we want to extend the Allora network to another class of topics: anomaly detection. In anomaly detection topics, consumers supply their own data to the network, and then the network decides whether this data is anomalous. A major difference to regression/classification problems is that a ground truth is generally not going to be available (and sometimes not even clearly defined), so this is an example of an unsupervised problem.
To start with, we should figure out what the main changes relative to regression and classification topics are and how we want to deal with them. Then we can implement this in the simulator, optimize parameters, and test whether everything works the way we hope.