Hands-On Machine Learning for Algorithmic Trading

Data mining for feature extraction

The cost-effective evaluation of large, complex datasets requires the detection of signals at scale. There are several examples throughout the book:

• Information theory is a useful tool to extract features that capture potential signals and can be used in ML models. In Chapter 4, Alpha Factor Research we use mutual information to assess the potential values of individual features for a supervised learning algorithm to predict asset returns.
• In Chapter 12, Unsupervised Learning, we introduce various techniques to create features from high-dimensional datasets. In Chapter 14, Topic Modeling, we apply these techniques to text data.
• We emphasize model-specific ways to gain insights into the predictive power ...