DefaultHyperOpts --> DefaultHyperOpt; hyperopts --> hyperopt where it's not correct
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@@ -10,12 +10,12 @@ Hyperopt requires historic data to be available, just as backtesting does.
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To learn how to get data for the pairs and exchange you're interrested in, head over to the [Data Downloading](data-download.md) section of the documentation.
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!!! Bug
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Hyperopt will crash when used with only 1 CPU Core as found out in [Issue #1133](https://github.com/freqtrade/freqtrade/issues/1133)
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Hyperopt can crash when used with only 1 CPU Core as found out in [Issue #1133](https://github.com/freqtrade/freqtrade/issues/1133)
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## Prepare Hyperopting
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Before we start digging into Hyperopt, we recommend you to take a look at
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an example hyperopt file located into [user_data/hyperopts/](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt.py)
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the sample hyperopt file located in [user_data/hyperopts/](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt.py).
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Configuring hyperopt is similar to writing your own strategy, and many tasks will be similar and a lot of code can be copied across from the strategy.
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@@ -64,9 +64,9 @@ multiple guards. The constructed strategy will be something like
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"*buy exactly when close price touches lower bollinger band, BUT only if
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ADX > 10*".
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If you have updated the buy strategy, ie. changed the contents of
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`populate_buy_trend()` method you have to update the `guards` and
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`triggers` hyperopts must use.
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If you have updated the buy strategy, i.e. changed the contents of
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`populate_buy_trend()` method, you have to update the `guards` and
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`triggers` your hyperopt must use correspondingly.
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#### Sell optimization
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@@ -82,7 +82,7 @@ To avoid naming collisions in the search-space, please prefix all sell-spaces wi
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#### Using ticker-interval as part of the Strategy
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The Strategy exposes the ticker-interval as `self.ticker_interval`. The same value is available as class-attribute `HyperoptName.ticker_interval`.
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In the case of the linked sample-value this would be `SampleHyperOpts.ticker_interval`.
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In the case of the linked sample-value this would be `SampleHyperOpt.ticker_interval`.
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## Solving a Mystery
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