Models & Versions


In Aporia, a model is any system that can make predictions and can be improved through the use of data.
We use this broad definition in order to support a large number of use cases. Some examples of a model include:
  • a simple Pytorch model
  • an ensemble of 15 XGBoost models, 37 LightGBM models, and a few deterministic algorithms
  • or even an evolutionary algorithm
Aporia models usually serve specific business use cases: Fraud Detection, Credit Risk, Patient Diagnosis, Churn Prediction, LTV, etc.

Model Version

Each model in Aporia can have different version. When you (re)train your model or update a model's schema you should create a new model version in Aporia (via the Versions page or SDK).
When creating a new model version in Aporia, you'll be able to specify the model version's schema - a definition of the inputs and outputs of the model.