November 2022
Intermediate to advanced
392 pages
10h 8m
Chinese
Content preview from Python算法交易
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通过机器学习预测市场动向
｜
159
图 5-8：GDX ETF 的总表现和基于回归的策略（七个滞后，样本外，扣除交易成本后）
5.2
使用机器学习进行市场动向预测
如今，
Python
生态系统在机器学习领域提供了许多软件包。其中最流行的是
scikit-learn
[
请参见
scikit-learn
主页（
http://scikit-learn.org
）
]
，它也是记录最
完整和维护最完善的软件包之一。本部分首先介绍基于线性回归的程序包的
API
，
跟上一部分的结果一样。然后，继续使用逻辑回归作为分类算法来解决预测未来市
场方向的问题。
5.2.1 scikit-learn
的线性回归
为了介绍
scikit-learn
API
，重新介绍本章介绍的预测方法背后的基本思想是富有
成效的。数据准备与仅使用
NumPy
相同：
In [61]: x = np.arange(12)
In [62]: x
Out[62]: array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])
In [63]: lags = 3
160
｜
第
5
章
In [64]: m = np.zeros((lags + 1, len(x) - lags))
In [65]: m[lags] = x[lags:]
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