How to Tune a Machine Learning Algorithm in Weka
Last Updated on August 22, 2019
Weka is the perfect platform for learning machine learning. It provides a graphical user interface for exploring and experimenting with machine learning algorithms on datasets, without you having to worry about the mathematics or the programming.
In a previous post we looked at how to design and run an experiment with 3 algorithms on a dataset and how to analyse and report the results.
Manhattan Skyline, because we are going to be looking at using Manhattan distance with the k-nearest neighbours algorithm.
Photo by Tim Pearce, Los Gatos, some rights reserved.
In this post you will discover how to use Weka Experimenter to improve your results and get the most out of a machine learning algorithm. If you follow along the step-by-step instructions, you will design and run your an algorithm tuning machine learning experiment in under five minutes.
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