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Merge pull request #11182 from 14790897/fix-docs-link-error

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fix: link error in strategy-customization
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Matthias
2025-01-04 17:14:33 +01:00
committed by GitHub
parent 046e1534f3 3682fcba4d
commit 37c10c9b06
1 changed files with 3 additions and 3 deletions
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6
docs/strategy-customization.md
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@@ -545,7 +545,7 @@ def informative_pairs(self):
]
```
A full sample can be found [in the DataProvider section](#complete-data-provider-sample).
A full sample can be found [in the DataProvider section](#complete-dataprovider-sample).
!!! Warning
As these pairs will be refreshed as part of the regular whitelist refresh, it's best to keep this list short.
@@ -576,7 +576,7 @@ To easily define informative pairs, use the `@informative` decorator. All decora
and do not have access to data from other informative pairs. However, all informative dataframes for each pair are merged and passed to main `populate_indicators()` method.
!!! Note
Do not use the `@informative` decorator if you need to use data from one informative pair when generating another informative pair. Instead, define informative pairs manually as described [in the DataProvider section](#complete-data-provider-sample).
Do not use the `@informative` decorator if you need to use data from one informative pair when generating another informative pair. Instead, define informative pairs manually as described [in the DataProvider section](#complete-dataprovider-sample).
When hyperopting, use of the hyperoptable parameter `.value` attribute is not supported. Please use the `.range` attribute. See [optimizing an indicator parameter](hyperopt.md#optimizing-an-indicator-parameter) for more information.
@@ -710,7 +710,7 @@ Options:
- Merge the dataframe without lookahead bias
- Forward-fill (optional)
For a full sample, please refer to the [complete data provider example](#complete-data-provider-sample) below.
For a full sample, please refer to the [complete data provider example](#complete-dataprovider-sample) below.
All columns of the informative dataframe will be available on the returning dataframe in a renamed fashion: