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@@ -2459,7 +2459,7 @@ will cause the algorithm to fail in live/dry mode. In order to add generalized f
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<td><code>df['%%*']</code></td>
<td>Any dataframe column prepended with <code>%%</code> in <code>feature_engineering_*()</code> is treated as a training feature, just the same as the above <code>%</code> prepend. However, in this case, the features are returned back to the strategy for FreqUI/plot-dataframe plotting and monitoring in Dry/Live/Backtesting <br> <strong>Datatype:</strong> Depends on the feature created by the user. Please note that features created in <code>feature_engineering_expand()</code> will have automatic FreqAI naming schemas depending on the expansions that you configured (i.e. <code>include_timeframes</code>, <code>include_corr_pairlist</code>, <code>indicators_periods_candles</code>, <code>include_shifted_candles</code>). So if you want to plot <code>%%-rsi</code> from <code>feature_engineering_expand_all()</code>, the final naming scheme for your plotting config would be: <code>%%-rsi-period_10_ETH/USDT:USDT_1h</code> for the <code>rsi</code> feature with <code>period=10</code>, <code>timeframe=1h</code>, and <code>pair=ETH/USDT:USDT</code> (the <code>:USDT</code> is added if you are using futures pairs). It is useful to simply add <code>print(dataframe.columns)</code> in your <code>populate_indicators()</code> after <code>self.freqai.start()</code> to see the full list of available features that are returned to the strategy for plotting purposes.</td>
<td>Any dataframe column prepended with <code>%%</code> in <code>feature_engineering_*()</code> is treated as a training feature, just the same as the above <code>%</code> prepend. However, in this case, the features are returned back to the strategy for FreqUI/plot-dataframe plotting and monitoring in Dry/Live/Backtesting <br> <strong>Datatype:</strong> Depends on the feature created by the user. <br><em>Please note</em> that features created in <code>feature_engineering_expand()</code> will have automatic FreqAI naming schemas depending on the expansions that you configured (i.e. <code>include_timeframes</code>, <code>include_corr_pairlist</code>, <code>indicators_periods_candles</code>, <code>include_shifted_candles</code>). So if you want to plot <code>%%-rsi</code> from <code>feature_engineering_expand_all()</code>, the final naming scheme for your plotting config would be: <code>%%-rsi-period_10_ETH/USDT:USDT_1h</code> for the <code>rsi</code> feature with <code>period=10</code>, <code>timeframe=1h</code>, and <code>pair=ETH/USDT:USDT</code> (the <code>:USDT</code> is added if you are using futures pairs). It is useful to simply add <code>print(dataframe.columns)</code> in your <code>populate_indicators()</code> after <code>self.freqai.start()</code> to see the full list of available features that are returned to the strategy for plotting purposes.</td>
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