docs: refine README.md

Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>

diff --git a/README.md b/README.md
index 554769e857ab61996284bcd0ebd33618bb0128e5..f6c9f88ceb3b5f0fd04840974ab44149f3398917 100644 (file)
--- a/README.md
+++ b/README.md
@@ -68,7 +68,7 @@ docker compose up -d --build
 | freqai.extrema_smoothing.bandwidth                   | 1.0                           | float > 0                                                                                                                                  | Gaussian bandwidth for `nadaraya_watson` smoothing.                                                                                                                                                                                                                                                                                                                     |
 | _Extrema weighting_                                  |                               |                                                                                                                                            |                                                                                                                                                                                                                                                                                                                                                                         |
 | freqai.extrema_weighting.strategy                    | `none`                        | enum {`none`,`amplitude`,`amplitude_threshold_ratio`,`volume_rate`,`speed`,`efficiency_ratio`,`volume_weighted_efficiency_ratio`,`hybrid`} | Extrema weighting source: unweighted (`none`), swing amplitude (`amplitude`), swing amplitude / median volatility-threshold ratio (`amplitude_threshold_ratio`), swing volume per candle (`volume_rate`), swing speed (`speed`), swing efficiency ratio (`efficiency_ratio`), swing volume-weighted efficiency ratio (`volume_weighted_efficiency_ratio`), or `hybrid`. |
-| freqai.extrema_weighting.source_weights              | `{}`                          | dict[str, float]                                                                                                                           | Weights on extrema extrema weighting sources for `hybrid`.                                                                                                                                                                                                                                                                                                              |
+| freqai.extrema_weighting.source_weights              | `{}`                          | dict[str, float]                                                                                                                           | Weights on extrema weighting sources for `hybrid`.                                                                                                                                                                                                                                                                                                                      |
 | freqai.extrema_weighting.aggregation                 | `weighted_sum`                | enum {`weighted_sum`,`geometric_mean`}                                                                                                     | Aggregation method applied to weighted extrema weighting sources for `hybrid`.                                                                                                                                                                                                                                                                                          |
 | freqai.extrema_weighting.aggregation_normalization   | `none`                        | enum {`minmax`,`sigmoid`,`softmax`,`l1`,`l2`,`rank`,`none`}                                                                                | Normalization method applied to the aggregated extrema weighting source for `hybrid`.                                                                                                                                                                                                                                                                                   |
 | freqai.extrema_weighting.standardization             | `none`                        | enum {`none`,`zscore`,`robust`,`mmad`}                                                                                                     | Standardization method applied to weights before normalization. `none`=no standardization, `zscore`=(w-μ)/σ, `robust`=(w-median)/IQR, `mmad`=(w-median)/MAD.                                                                                                                                                                                                            |