adelorenzo/stable
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Merge pull request #8009 from freqtrade/robcaulk-patch-1

Browse Source 
Update freqai-reinforcement-learning.md
This commit is contained in:
Matthias 2023-01-12 23:33:54 +01:00 committed by GitHub
commit 5d45adb37d
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 5 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

9
docs/freqai-reinforcement-learning.md
View File

@ -58,11 +58,12 @@ where `ReinforcementLearner` will use the templated `ReinforcementLearner` from
Most of the function remains the same as for typical Regressors, however, the function above shows how the strategy must pass the raw price data to the agent so that it has access to raw OHLCV in the training environment:
```python
def feature_engineering_standard():
# The following features are necessary for RL models
informative[f"%-{pair}raw_close"] = informative["close"]
informative[f"%-{pair}raw_open"] = informative["open"]
informative[f"%-{pair}raw_high"] = informative["high"]
informative[f"%-{pair}raw_low"] = informative["low"]
informative[f"%-raw_close"] = informative["close"]
informative[f"%-raw_open"] = informative["open"]
informative[f"%-raw_high"] = informative["high"]
informative[f"%-raw_low"] = informative["low"]
```
Finally, there is no explicit "label" to make - instead it is necessary to assign the `&-action` column which will contain the agent's actions when accessed in `populate_entry/exit_trends()`. In the present example, the neutral action to 0. This value should align with the environment used. FreqAI provides two environments, both use 0 as the neutral action.