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- 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 convenience method create_instances_from_lists to weka.core.dataset module to easily create an Instances object from numeric lists (x and y)
- added get_object_tags method to Tags class from module weka.core.classes, to allow obtaining weka.core.Tag array from the method of a JavaObject rather than a static field (MultiSearch)
- updated MultiSearch wrapper in module weka.classifiers to work with the multi-search package version 2016.1.15 or later
- BibTeX Entry: Download
- Supported Operating Systems: Agnostic
- Data Formats: Arff, Csv, Libsvm, Xrff
- Tags: Machine Learning, Weka
- Archive: download here
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