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add doc section for classifier

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Robert Caulk 2022-08-06 09:45:26 +02:00
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@ -411,9 +411,17 @@ The Freqai strategy requires the user to include the following lines of code in
The user should also include `populate_any_indicators()` from `templates/FreqaiExampleStrategy.py` which builds The user should also include `populate_any_indicators()` from `templates/FreqaiExampleStrategy.py` which builds
the feature set with a proper naming convention for the IFreqaiModel to use later. the feature set with a proper naming convention for the IFreqaiModel to use later.
### Setting classifier targets
FreqAI includes a the `CatboostClassifier` via the flag `--freqaimodel CatboostClassifier`. Typically, the user would set the targets using strings:
```python
df['&s-up_or_down'] = np.where( df["close"].shift(-100) > df["close"], 'up', 'down')
```
### Building an IFreqaiModel ### Building an IFreqaiModel
FreqAI has multiple example prediction model based libraries such as `Catboost` regression (`freqai/prediction_models/CatboostPredictionModel.py`) and `LightGBM` regression. FreqAI has multiple example prediction model based libraries such as `Catboost` regression (`freqai/prediction_models/CatboostRegressor.py`) and `LightGBM` regression.
However, users can customize and create their own prediction models using the `IFreqaiModel` class. However, users can customize and create their own prediction models using the `IFreqaiModel` class.
Users are encouraged to inherit `train()` and `predict()` to let them customize various aspects of their training procedures. Users are encouraged to inherit `train()` and `predict()` to let them customize various aspects of their training procedures.