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improve docs, update doc strings

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This commit is contained in:
robcaulk
2023-06-10 13:11:47 +02:00
parent d9bdd879ab
commit 41e37f9d32
3 changed files with 13 additions and 6 deletions
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11
docs/strategy_migration.md
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@@ -736,7 +736,7 @@ If you have created your own custom `IFreqaiModel` with a custom `train()`/`pred
The conversion involves first removing `data_cleaning_train/predict()` and replacing them with a `define_data_pipeline()` and `define_label_pipeline()` function to your `IFreqaiModel` class:
```python linenums="1" hl_lines="11-14 43-44 51-52"
```python linenums="1" hl_lines="11-14 47-49 55-57"
class MyCoolFreqaiModel(BaseRegressionModel):
"""
Some cool custom IFreqaiModel you made before Freqtrade version 2023.6
@@ -773,9 +773,13 @@ class MyCoolFreqaiModel(BaseRegressionModel):
dd["train_labels"], _, _ = dk.label_pipeline.fit_transform(dd["train_labels"])
dd["test_labels"], _, _ = dk.label_pipeline.transform(dd["test_labels"])
# ... your custom code
return model
def predict(
self, unfiltered_df: DataFrame, dk: FreqaiDataKitchen, **kwargs
) -> Tuple[DataFrame, npt.NDArray[np.int_]]: # 37
) -> Tuple[DataFrame, npt.NDArray[np.int_]]:
# ... your custom stuff
@@ -798,6 +802,9 @@ class MyCoolFreqaiModel(BaseRegressionModel):
else:
dk.DI_values = np.zeros(len(outliers.index))
dk.do_predict = outliers.to_numpy()
# ... your custom code
return (pred_df, dk.do_predict)
```

4
freqtrade/freqai/base_models/BaseClassifierModel.py
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@@ -17,8 +17,8 @@ logger = logging.getLogger(__name__)
class BaseClassifierModel(IFreqaiModel):
"""
Base class for regression type models (e.g. Catboost, LightGBM, XGboost etc.).
User *must* inherit from this class and set fit() and predict(). See example scripts
such as prediction_models/CatboostPredictionModel.py for guidance.
User *must* inherit from this class and set fit(). See example scripts
such as prediction_models/CatboostClassifier.py for guidance.
"""
def train(

4
freqtrade/freqai/base_models/BaseRegressionModel.py
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@@ -16,8 +16,8 @@ logger = logging.getLogger(__name__)
class BaseRegressionModel(IFreqaiModel):
"""
Base class for regression type models (e.g. Catboost, LightGBM, XGboost etc.).
User *must* inherit from this class and set fit() and predict(). See example scripts
such as prediction_models/CatboostPredictionModel.py for guidance.
User *must* inherit from this class and set fit(). See example scripts
such as prediction_models/CatboostRegressor.py for guidance.
"""
def train(