How to Tune Algorithm Parameters with Scikit-Learn

Last Updated on August 21, 2019

Machine learning models are parameterized so that their behavior can be tuned for a given problem.

Models can have many parameters and finding the best combination of parameters can be treated as a search problem.

In this post, you will discover how to tune the parameters of machine learning algorithms in Python using the scikit-learn library.

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• Update Jan/2017: Updated to reflect changes to the scikit-learn API in version 0.18.

Machine Learning Algorithm Parameters

Algorithm tuning is a final step in the process of applied machine learning before presenting results.

It is sometimes called Hyperparameter optimization where the algorithm parameters are referred to as hyperparameters whereas the coefficients
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