"""
Hidden Markov Model / state-space experiments on sequential features.

TODO:
  - Use hmmlearn or custom HMM on (SEQ_LEN, n_feat) windows or on latent PCA factors
  - Map inferred states to regime labels; use as features for XGBoost or for entry filters
  - Cross-validate strictly in time (walk-forward) like 6_train_xgb_daily.py
"""

from __future__ import annotations

# Optional dependency: hmmlearn — add when first experiment lands.