more updates

docker-compose.yml

@@ -46,8 +46,8 @@ services:
       RAIN_TUNE_HYPERPARAMETERS: "true"
       RAIN_MAX_HYPERPARAM_TRIALS: "12"
       RAIN_CALIBRATION_METHODS: "none,sigmoid,isotonic"
-      RAIN_THRESHOLD_POLICY: "validation"
-      RAIN_WALK_FORWARD_FOLDS: "0"
+      RAIN_THRESHOLD_POLICY: "walk_forward"
+      RAIN_WALK_FORWARD_FOLDS: "4"
       RAIN_ALLOW_EMPTY_DATA: "true"
       RAIN_MODEL_PATH: "/app/models/rain_model.pkl"
       RAIN_MODEL_BACKUP_PATH: "/app/models/rain_model.pkl.last_good"

docs/rain_model_runbook.md

@@ -143,7 +143,7 @@ The script exits non-zero on failure, so it can directly drive alerting.
 
 Recommended production defaults:
 - Enable tuning daily or weekly (`RAIN_TUNE_HYPERPARAMETERS=true`)
-- Keep walk-forward folds `0` in continuous mode, run fold backtests in scheduled evaluation jobs
+- Set `RAIN_THRESHOLD_POLICY=walk_forward` with `RAIN_WALK_FORWARD_FOLDS=4` for temporally robust threshold selection
 
 ## 8) Auto-Recommend Candidate
 

scripts/run_rain_ml_worker.py

@@ -303,7 +303,7 @@ def load_config() -> WorkerConfig:
         tune_hyperparameters=read_env_bool("RAIN_TUNE_HYPERPARAMETERS", False),
         max_hyperparam_trials=read_env_int("RAIN_MAX_HYPERPARAM_TRIALS", 12),
         calibration_methods=read_env("RAIN_CALIBRATION_METHODS", "none,sigmoid,isotonic"),
-        threshold_policy=read_env("RAIN_THRESHOLD_POLICY", "validation"),
+        threshold_policy=read_env("RAIN_THRESHOLD_POLICY", "walk_forward"),
         walk_forward_folds=read_env_int("RAIN_WALK_FORWARD_FOLDS", 0),
         allow_empty_data=read_env_bool("RAIN_ALLOW_EMPTY_DATA", True),
         dataset_path_template=read_env(