Evaluate the Performance of Machine Learning Algorithms in Python using Resampling

Last Updated on August 28, 2020

You need to know how well your algorithms perform on unseen data.

The best way to evaluate the performance of an algorithm would be to make predictions for new data to which you already know the answers. The second best way is to use clever techniques from statistics called resampling methods that allow you to make accurate estimates for how well your algorithm will perform on new data.

In this post you will discover how you can estimate the accuracy of your machine learning algorithms using resampling methods in Python and scikit-learn.

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• Update Jan/2017: Updated to reflect changes to the scikit-learn API in version 0.18.
• Update Oct/2017: Updated print statements to work with Python 3.
• Update Mar/2018: Added alternate link to download the dataset as the original appears to have been taken down.