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Hands-On Machine Learning for Algorithmic Trading
book

Hands-On Machine Learning for Algorithmic Trading

by Stefan Jansen
December 2018
Beginner to intermediate
684 pages
21h 9m
English
Packt Publishing
Content preview from Hands-On Machine Learning for Algorithmic Trading

Parameter tuning using GridSearchCV and pipeline

Since hyperparameter tuning is a key ingredient of the machine learning workflow, there are tools to automate this process. The sklearn library includes a GridSearchCV interface that cross-validates all combinations of parameters in parallel, captures the result, and automatically trains the model using the parameter setting that performed best during cross-validation on the full dataset.

In practice, the training and validation sets often require some processing prior to cross-validation. Scikit-learn offers the Pipeline to also automate any requisite feature-processing steps in the automated hyperparameter tuning facilitated by GridSearchCV.

You can look at the implementation examples in ...

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Publisher Resources

ISBN: 9781789346411Supplemental Content