Difference between weka and hortonwors sandbox
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hortonwors is intended to support scalable machine learning. As such, it does not support all different algorithms, only a small number that are known to work in a scalable fashion. Mahout is particularly strong in recommendations.
Weka is intended to support a broad range of algorithms, all implemented in an in-memory fashion. Scalability beyond in-memory sizes is explicitly not a goal. Weka also has a graphical interface that controls essentially all functions.
There is also a difference in licenses. hortonwors licensed which means that you can incorporate pieces of it into your own software regardless of whether you want to release your source code. Weka is GPL'ed which means that incorporating it into your software forces you to release source code for any software you package with Weka components.
Weka is intended to support a broad range of algorithms, all implemented in an in-memory fashion. Scalability beyond in-memory sizes is explicitly not a goal. Weka also has a graphical interface that controls essentially all functions.
There is also a difference in licenses. hortonwors licensed which means that you can incorporate pieces of it into your own software regardless of whether you want to release your source code. Weka is GPL'ed which means that incorporating it into your software forces you to release source code for any software you package with Weka components.
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