refactor(ml): split monolith into 9 sub-crates + delete dead code

Extract 9 new sub-crates from the ml monolith to enable parallel
compilation across the workspace:

New crates (this commit):
- ml-features (282 tests): feature engineering, 21 modules
- ml-labeling (45 tests): triple barrier, meta-labeling, fractional diff
- ml-ensemble (116 tests): ensemble coordination, voting, confidence
- ml-hyperopt (47 tests): core PSO/TPE optimizer, parameter space
- ml-checkpoint (41 tests): checkpoint persistence, compression, signing
- ml-regime (68 tests): CUSUM, Bayesian changepoint, regime classification
- ml-data-validation (67 tests): FDR correction, CPCV, data quality
- ml-risk (33 tests): neural VaR, Kelly criterion, circuit breakers
- ml-validation (43 tests): statistical validation, walk-forward, DSR

Extended existing crates:
- ml-dqn: added evaluation/ (backtesting engine, metrics, reports)
  and checkpoint implementation
- ml-supervised: added checkpoint implementations
- ml-core: added shared types needed by new sub-crates

Pattern: each module in ml/ becomes a thin facade (pub use subcrate::*)
with bridge modules staying in ml for cross-model adapter code.

Dead code deleted (~7K lines):
- 13 undeclared files in microstructure/ (never compiled)
- 7 undeclared files + tests/ in risk/ (never compiled)
- parquet_io, cache_service, cache_storage, minio_integration (unused)
- extraction_wave_d_impl.rs (bare fn outside impl block)

All 2,746 sub-crate tests + 951 ml tests pass.
Full workspace builds clean.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

crates/ml/Cargo.toml

@@ -28,7 +28,7 @@ simd = []  # SIMD without heavy dependencies
 
 # Storage and memory management features
 gc = []  # Garbage collection features
-s3-storage = ["aws-config", "aws-sdk-s3", "aws-types", "aws-credential-types", "urlencoding"]  # S3 storage backend with AWS SDK
+s3-storage = ["ml-checkpoint/s3-storage", "aws-config", "aws-sdk-s3", "aws-types", "aws-credential-types", "urlencoding"]  # S3 storage backend with AWS SDK
 cuda = ["candle-core/cuda", "candle-core/cudnn", "candle-nn/cuda", "candle-nn/cudnn"]  # CUDA support (includes LSTM sigmoid ops) - OPTIONAL for CI/Docker
 nccl = ["cuda"]  # NCCL multi-GPU data parallelism (requires NCCL library + cudarc nccl feature)
 
@@ -69,9 +69,18 @@ colored = "2.1"  # Terminal color output for evaluation reports
 
 # Internal workspace crates
 ml-core.workspace = true
+ml-ensemble.workspace = true
 ml-dqn.workspace = true
 ml-ppo.workspace = true
 ml-supervised.workspace = true
+ml-hyperopt.workspace = true
+ml-features.workspace = true
+ml-labeling.workspace = true
+ml-regime.workspace = true
+ml-checkpoint.workspace = true
+ml-data-validation.workspace = true
+ml-validation.workspace = true
+ml-risk.workspace = true
 config.workspace = true
 common = { workspace = true, features = ["questdb"] }
 risk = { path = "../risk" }