docs(README.md): fix minmax_range type in extrema_weighting config table

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

diff --git a/README.md b/README.md
index e82d48861d158a3f646bf39ec5a21243de3eaf77..353f3d3ac755a4549e9f242d259e17c2a9c82338 100644 (file)
--- a/README.md
+++ b/README.md
@@ -66,7 +66,7 @@ docker compose up -d --build
 | freqai.extrema_weighting.standardization             | `none`            | enum {`none`,`zscore`,`robust`}                                                                                                  | Standardization method applied before normalization. `none`=no standardization, `zscore`=(w-μ)/σ, `robust`=(w-median)/IQR.                                                                                                                                                                          |
 | freqai.extrema_weighting.robust_quantiles            | [0.25, 0.75]      | list[float] where 0 <= q_low < q_high <= 1                                                                                       | Quantile range for robust standardization, Q1 and Q3.                                                                                                                                                                                                                                               |
 | freqai.extrema_weighting.normalization               | `minmax`          | enum {`minmax`,`sigmoid`,`softmax`,`l1`,`l2`,`rank`,`none`}                                                                      | Normalization method for weights.                                                                                                                                                                                                                                                                   |
-| freqai.extrema_weighting.minmax_range                | [0.0, 1.0]        | list[float, float]                                                                                                               | Target range for minmax normalization, min and max.                                                                                                                                                                                                                                                 |
+| freqai.extrema_weighting.minmax_range                | [0.0, 1.0]        | list[float]                                                                                                                      | Target range for minmax normalization, min and max.                                                                                                                                                                                                                                                 |
 | freqai.extrema_weighting.sigmoid_scale               | 1.0               | float > 0                                                                                                                        | Scale parameter for sigmoid normalization, controls steepness.                                                                                                                                                                                                                                      |
 | freqai.extrema_weighting.softmax_temperature         | 1.0               | float > 0                                                                                                                        | Temperature parameter for softmax normalization: lower values sharpen distribution, higher values flatten it.                                                                                                                                                                                       |
 | freqai.extrema_weighting.rank_method                 | `average`         | enum {`average`,`min`,`max`,`dense`,`ordinal`}                                                                                   | Ranking method for rank normalization.                                                                                                                                                                                                                                                              |