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:

• The "packages" parameter of the "weka.core.jvm.start()" function can be used for specifying an alternative Weka home directory now as well
• added "train_test_split" method to "weka.core.Instances" class to easily create train/test splits
• "evaluate_train_test_split" method of "weka.classifiers.Evaluation" class now uses the "train_test_split" method

BibTeX Entry: Download

Supported Operating Systems: Agnostic

Data Formats: Arff, Csv, Libsvm, Xrff

Tags: Machine Learning, Weka

Archive: download here

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