freqtrade_origin/docs/freqai-developers.md

Development

The class structure and details algorithmic overview is depicted in the following diagram:

As shown, there are three distinct objects comprising FreqAI:

• IFreqaiModel
  • Singular persistent object containing all the necessary logic to collect data, store data, process data, engineer features, run training, and inference models.
• FreqaiDataKitchen
  • A non-persistent object which is created uniquely for each unique asset/model. Beyond metadata, it also contains a variety of data processing tools.
• FreqaiDataDrawer
  • Singular persistent object containing all the historical predictions, models, and save/load methods.

There are a variety of built-in prediction models which inherit directly from IFreqaiModel including:

• CatboostRegressor
• CatboostRegressorMultiTarget
• CatboostClassifier
• LightGBMRegressor
• LightGBMRegressorMultiTarget
• LightGBMClassifier
• XGBoostRegressor
• XGBoostRegressorMultiTarget
• XGBoostClassifier

Each of these have full access to all methods in IFreqaiModel. And can therefore, override any of those functions at will. However, advanced users will likely stick to overriding fit(), train(), predict(), and data_cleaning_train/predict().