Archive | Weka Machine Learning

Algorithm ranking when analyzing results in the Weka Experimenter

Improve Machine Learning Results with Boosting, Bagging and Blending Ensemble Methods in Weka

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 […]

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First Experiment

Design and Run your First Experiment in Weka

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. A powerful feature of Weka is the Weka Experimenter interface. Unlike the Weka Explorer that is for filtering data […]

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Weka Results for the ZeroR algorithm on the Iris flower dataset

How to Run Your First Classifier in Weka

Weka makes learning applied machine learning easy, efficient, and fun. It is a GUI tool that allows you to load datasets, run algorithms and design and run experiments with results statistically robust enough to publish. I recommend Weka to beginners in machine learning because it lets them focus on learning the process of applied machine learning rather […]

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Weka Explorer Interface with the Iris dataset loaded

What is the Weka Machine Learning Workbench

Machine learning is an iterative process rather than a linear process that requires each step to be revisited as more is learned about the problem under investigation. This iterative process can require using many different tools, programs and scripts for each process. A machine learning workbench is a platform or environment that supports and facilitates […]

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