模型训练实操

Lesson Overview

In "Machine Learning for Trading" → "模型训练", this lesson "模型训练实操" builds knowledge you can apply immediately.

训练实操记录版本、随机种子、样本量、指标与基线。准确率高不等于风险调整收益，交易阈值、费用和执行尚需独立研究。 按README运行→核train158/test67→检查标签边界→保存metrics→比较基线→不为凑高分修改测试。 本课作业：复现随机森林报告，写accuracy、precision、recall、AUC各自回答什么，并列两项真实市场限制。

Core Concepts

These points align with the video walkthrough—take notes as you watch.

• ▸训练实操记录版本、随机种子、样本量、指标与基线。准确率高不等于风险调整收益，交易阈值、费用和执行尚需独立研究。
• ▸按README运行→核train158/test67→检查标签边界→保存metrics→比较基线→不为凑高分修改测试。
• ▸本课作业：复现随机森林报告，写accuracy、precision、recall、AUC各自回答什么，并列两项真实市场限制。

Practical Application

After studying, complete the practice tasks below to move from understanding to doing.

• ▸Follow along in Jupyter or VS Code
• ▸Log how parameter changes affect backtest results
• ▸Submit a reproducible analysis notebook

FAQ

• ▸Q: How does this lesson fit the course? A: Part of "模型训练"—follow the curriculum order.
• ▸Q: What do I need? A: Demo account and notes; quant lessons need a Python environment.
• ▸Q: How do I know I've mastered it? A: Pass the quiz and explain three key points of 模型训练实操 on your own.