How to Tune Machine Learning Algorithms in Weka

Last Updated on December 11, 2019

You can get the most from a machine learning algorithm by tuning its parameters, called hyperparameters.

In this post you will discover how to tune machine learning algorithms with controlled experiments in Weka.

After reading this post you will know:

• The importance of improving the performance of machine learning models by algorithm tuning.
• How to design a controlled experiment to tune the hyperparameters of a machine learning algorithm.
• How to interpret the results from tuning an experiment using statistical significance.

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Improve Performance By Tuning

Machine learning algorithms can be configured to elicit different behavior.

This is useful because it allows their behavior to be adapted to the specifics of your machine learning problem.

This is also a difficulty because you must choose how
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