Make Better Predictions with Boosting, Bagging and Blending Ensembles in Weka

Last Updated on August 22, 2019

Weka is the perfect platform for studying 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 running 3 algorithms on a dataset and how to analyse and report the results. We also looked at how to design and run an experiment to tune the configuration of a machine learning algorithm

In this post you will discover how to use Weka Experimenter to improve your results by combining the results of multiple algorithms together into ensembles. If you follow along the step-by-step instructions, you will design and run your an ensemble machine learning experiment in under five minutes.

Kick-start your project with my new book Machine Learning Mastery With Weka, including step-by-step tutorials and clear screenshots for all examples.

1. Download Weka and Install

Visit the Weka Download page and
To finish reading, please visit source site