fix(quickadapter): align label prediction keep fraction default

diff --git a/README.md b/README.md
index 41f76161199eb4e9cea89c2b177e09022246cf20..14002bf38cdb782d903901d852868e17bf9a5804 100644 (file)
--- a/README.md
+++ b/README.md
@@ -122,7 +122,7 @@ docker compose up -d --build
 | freqai.label_prediction.threshold_method                       | `mean`                        | enum {`mean`,`isodata`,`li`,`minimum`,`otsu`,`triangle`,`yen`,`median`,`soft_extremum`}                                                                | Thresholding method for prediction thresholds.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
 | freqai.label_prediction.soft_extremum_alpha                    | 12.0                          | float >= 0                                                                                                                                             | Alpha for `soft_extremum` threshold method.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
 | freqai.label_prediction.outlier_quantile                       | 0.999                         | float (0,1)                                                                                                                                            | Quantile threshold for predictions outlier filtering.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
-| freqai.label_prediction.keep_fraction                          | 0.5                           | float (0,1]                                                                                                                                            | Fraction of extrema used for thresholds. 1 uses all, lower values keep only most significant. Applies to `rank_extrema` and `rank_peaks`; ignored for `partition`.                                                                                                                                                                                                                                                                                                                                                                                                       |
+| freqai.label_prediction.keep_fraction                          | 0.0075                        | float (0,1]                                                                                                                                            | Fraction of extrema used for thresholds. 1 uses all, lower values keep only most significant. Applies to `rank_extrema` and `rank_peaks`; ignored for `partition`.                                                                                                                                                                                                                                                                                                                                                                                                       |
 | _Optuna / HPO_                                                 |                               |                                                                                                                                                        |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
 | freqai.optuna_hyperopt.enabled                                 | false                         | bool                                                                                                                                                   | Enables HPO.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             |
 | freqai.optuna_hyperopt.sampler                                 | `tpe`                         | enum {`tpe`,`auto`}                                                                                                                                    | HPO sampler algorithm for `hp` namespace. `tpe` uses [TPESampler](https://optuna.readthedocs.io/en/stable/reference/samplers/generated/optuna.samplers.TPESampler.html) with multivariate, group, and constant_liar (when multiple workers), `auto` uses [AutoSampler](https://hub.optuna.org/samplers/auto_sampler).                                                                                                                                                                                                                                                    |

diff --git a/quickadapter/user_data/strategies/LabelTransformer.py b/quickadapter/user_data/strategies/LabelTransformer.py
index 8ec3a727fc83e87879d5f4144d14d27aa809257e..d1dd0497b80267b99d01f1cc30888fdfc3e686e1 100644 (file)
--- a/quickadapter/user_data/strategies/LabelTransformer.py
+++ b/quickadapter/user_data/strategies/LabelTransformer.py
@@ -200,7 +200,7 @@ DEFAULTS_LABEL_PREDICTION: Final[dict[str, Any]] = {
     "threshold_method": SKIMAGE_THRESHOLD_METHODS[0],  # "mean"
     "outlier_quantile": 0.999,
     "soft_extremum_alpha": 12.0,
-    "keep_fraction": 0.5,
+    "keep_fraction": 0.0075,
 }