Files
quant-trader-service/training/scripts/21_benchmark_nonlinear_models.py
T
Codex 9acb3460a1 Improve Trader V4 training pipeline
Align entry labels with max future edge, tune direction labeling, and harden regression evaluation.

Add training diagnostics, price-plan search, feature screening, and nonlinear benchmark scripts.
2026-06-27 19:57:29 +08:00

22 lines
657 B
Python

from __future__ import annotations
import argparse
import logging
from pathlib import Path
import _bootstrap # noqa: F401
from trader_training.nonlinear_benchmark import benchmark_nonlinear_models
def main() -> None:
parser = argparse.ArgumentParser(description="Run diagnostic nonlinear benchmarks for Direction and Entry.")
parser.add_argument("--run-id", required=True)
parser.add_argument("--data-root", required=True, type=Path)
args = parser.parse_args()
logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s event=%(message)s")
benchmark_nonlinear_models(args)
if __name__ == "__main__":
main()