set separate table sections in doc
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@ -67,6 +67,7 @@ freqtrade backtesting --config config_examples/config_freqai.example.json --stra
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## Configuring the bot
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## Configuring the bot
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### Parameter table
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The table below will list all configuration parameters available for `FreqAI`.
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The table below will list all configuration parameters available for `FreqAI`.
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Mandatory parameters are marked as **Required**, which means that they are required to be set in one of the possible ways.
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Mandatory parameters are marked as **Required**, which means that they are required to be set in one of the possible ways.
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| `live_trained_timestamp` | Useful if user wants to start from models trained during a *backtest*. The timestamp can be located in the `user_data/models` backtesting folder. This is not a commonly used parameter, leave undefined for most applications. <br> **Datatype:** positive integer.
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| `live_trained_timestamp` | Useful if user wants to start from models trained during a *backtest*. The timestamp can be located in the `user_data/models` backtesting folder. This is not a commonly used parameter, leave undefined for most applications. <br> **Datatype:** positive integer.
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| `fit_live_predictions_candles` | Computes target (label) statistics from prediction data, instead of from the training data set. Number of candles is the number of historical candles it uses to generate the statistics. <br> **Datatype:** positive integer.
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| `fit_live_predictions_candles` | Computes target (label) statistics from prediction data, instead of from the training data set. Number of candles is the number of historical candles it uses to generate the statistics. <br> **Datatype:** positive integer.
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| `purge_old_models` | Tell FreqAI to delete obsolete models. Otherwise, all historic models will remain on disk. Defaults to False. <br> **Datatype:** boolean.
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| `purge_old_models` | Tell FreqAI to delete obsolete models. Otherwise, all historic models will remain on disk. Defaults to False. <br> **Datatype:** boolean.
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| | **Feature Parameters**
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| `expiration_hours` | Ask FreqAI to avoid making predictions if a model is more than `expiration_hours` old. Defaults to 0 which means models never expire. <br> **Datatype:** positive integer.
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| `expiration_hours` | Ask FreqAI to avoid making predictions if a model is more than `expiration_hours` old. Defaults to 0 which means models never expire. <br> **Datatype:** positive integer.
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| | **Feature Parameters**
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| | **Feature Parameters**
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| `feature_parameters` | A dictionary containing the parameters used to engineer the feature set. Details and examples shown [here](#building-the-feature-set) <br> **Datatype:** dictionary.
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| `feature_parameters` | A dictionary containing the parameters used to engineer the feature set. Details and examples shown [here](#building-the-feature-set) <br> **Datatype:** dictionary.
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| `learning_rate` | A common parameter among regressors which sets the boosting learning rate. <br> **Datatype:** float.
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| `learning_rate` | A common parameter among regressors which sets the boosting learning rate. <br> **Datatype:** float.
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| `n_jobs`, `thread_count`, `task_type` | Different libraries use different parameter names to control the number of threads used for parallel processing or whether or not it is a `task_type` of `gpu` or `cpu`. <br> **Datatype:** float.
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| `n_jobs`, `thread_count`, `task_type` | Different libraries use different parameter names to control the number of threads used for parallel processing or whether or not it is a `task_type` of `gpu` or `cpu`. <br> **Datatype:** float.
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### Return values for use in strategy
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Here are the values you can expect to receive inside the dataframe returned by FreqAI:
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Here are the values you can expect to receive inside the dataframe returned by FreqAI:
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| Parameter | Description |
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| Parameter | Description |
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