Description:

A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls. Offers all major APIs, like data generators, loaders, savers, filters, classifiers, clusterers, attribute selection, associations and experiments. Weka packages can be listed/installed/uninstalled as well. It does not provide any graphical frontend, but some basic plotting and graph visualizations are available through matplotlib and pygraphviz.

Changes to previous version:

• added "get_class" method to "weka.core.utils" which returns the Python class object associated with the classname in dot-notation
• "from_commandline" method in "weka.core.utils" now takes an optional "classname" argument, which is the classname (in dot-notation) of the wrapper class to return - instead of the generic "OptionHandler"
• added "Kernel" and "KernelClassifier" convenience classes to better handle kernel based classifiers

BibTeX Entry: Download

Supported Operating Systems: Agnostic

Data Formats: Arff, Csv, Libsvm, Xrff

Tags: Machine Learning, Weka

Archive: download here

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