mirror of
https://github.com/freqtrade/freqtrade.git
synced 2024-11-10 10:21:59 +00:00
give beta testers more information in the doc
This commit is contained in:
parent
a7029e35b5
commit
a8022c104a
|
@ -41,6 +41,23 @@ in the model.
|
|||
intermediate performance of the model during training. This data does not
|
||||
directly influence nodal weights within the model.
|
||||
|
||||
## Install prerequisites
|
||||
|
||||
Use `pip` to install the prerequisities with:
|
||||
|
||||
`pip install -r requirements-freqai.txt`
|
||||
|
||||
## Running from the example files
|
||||
|
||||
An example strategy, example prediction model, and example config can all be found in
|
||||
`freqtrade/templates/ExampleFreqaiStrategy.py`, `freqtrade/templates/ExamplePredictionModel.py`,
|
||||
`config_examples/config_freqai.example.json`, respectively. Assuming the user has downloaded
|
||||
the necessary data, Freqai can be executed from these templates with:
|
||||
|
||||
`freqtrade backtesting --config config_examples/config_freqai.example.json--strategy
|
||||
ExampleFreqaiStrategy --freqaimodel ExamplePredictionModel
|
||||
--freqaimodel-path freqtrade/templates --strategy-path freqtrade/templates`
|
||||
|
||||
## Configuring the bot
|
||||
### Example config file
|
||||
The user interface is isolated to the typical config file. A typical Freqai
|
||||
|
|
|
@ -113,8 +113,6 @@ class FreqaiDataKitchen:
|
|||
with open(self.model_path / str(self.model_filename + "_metadata.json"), "r") as fp:
|
||||
self.data = json.load(fp)
|
||||
self.training_features_list = self.data["training_features_list"]
|
||||
# if self.data.get("training_features_list"):
|
||||
# self.training_features_list = [*self.data.get("training_features_list")]
|
||||
|
||||
self.data_dictionary["train_features"] = pd.read_pickle(
|
||||
self.model_path / str(self.model_filename + "_trained_df.pkl")
|
||||
|
|
|
@ -42,8 +42,8 @@ class ExamplePredictionModel(IFreqaiModel):
|
|||
|
||||
def train(self, unfiltered_dataframe: DataFrame, metadata: dict) -> Tuple[DataFrame, DataFrame]:
|
||||
"""
|
||||
Filter the training data and train a model to it. Train makes heavy use of the datahandler
|
||||
for storing, saving, loading, and managed.
|
||||
Filter the training data and train a model to it. Train makes heavy use of the datahkitchen
|
||||
for storing, saving, loading, and analyzing the data.
|
||||
:params:
|
||||
:unfiltered_dataframe: Full dataframe for the current training period
|
||||
:metadata: pair metadata from strategy.
|
||||
|
|
Loading…
Reference in New Issue
Block a user