Add column description to hyperopt documentation
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@ -31,7 +31,6 @@ Depending on the space you want to optimize, only some of the below are required
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* Optional but recommended
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* Optional but recommended
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* copy `populate_buy_trend` from your strategy - otherwise default-strategy will be used
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* copy `populate_buy_trend` from your strategy - otherwise default-strategy will be used
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* copy `populate_sell_trend` from your strategy - otherwise default-strategy will be used
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* copy `populate_sell_trend` from your strategy - otherwise default-strategy will be used
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* Add custom loss-function `hyperopt_loss_custom` (Details below)
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### 1. Install a Custom Hyperopt File
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### 1. Install a Custom Hyperopt File
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@ -200,7 +199,9 @@ class SuperDuperHyperOptLoss(IHyperOptLoss):
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Currently, the arguments are:
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Currently, the arguments are:
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* `results`: DataFrame containing the result
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* `results`: DataFrame containing the result
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The following columns are available in results (corresponds to the output of backtesting):
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`pair, profit_percent, profit_abs, open_time, close_time, open_index, close_index, trade_duration, open_at_end, open_rate, close_rate, sell_reason`
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* `trade_count`: Amount of trades (identical to `len(results)`)
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* `trade_count`: Amount of trades (identical to `len(results)`)
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* `min_date`: Start date of the hyperopting TimeFrame
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* `min_date`: Start date of the hyperopting TimeFrame
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* `min_date`: End date of the hyperopting TimeFrame
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* `min_date`: End date of the hyperopting TimeFrame
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