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. A simple workflow engine was added with release 0.3.0.

Changes to previous version:

• added support for weka.core.BatchPredictor to class Classifier in module weka.classifiers
• upgraded Weka to revision 12410 (post 3.7.13) to avoid performance bottleneck when using setOptions method
• fixed class SetupGenerator from module weka.core.classes
• added load_any_file method to the weka.core.converters module
• added save_any_file method to the weka.core.converters module
• if GridSearch instantiation (module weka.classifiers) fails, it now outputs message whether package installed and JVM with package support started

BibTeX Entry: Download

Supported Operating Systems: Agnostic

Data Formats: Arff, Csv, Libsvm, Xrff

Tags: Machine Learning, Weka

Archive: download here

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