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- Description:
A thin Python3 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:
- plot_learning_curve method of module weka.plot.classifiers now accepts a list of test sets; * is index of test set in label template string
- added missing_value() methods to weka.core.dataset module and Instance class
- output variable y for convenience method create_instances_from_lists in module weka.core.dataset is now optional
- added convenience method create_instances_from_matrices to weka.core.dataset module to easily create an Instances object from numpy matrices (x and y)
- BibTeX Entry: Download
- Supported Operating Systems: Agnostic
- Data Formats: Arff, Csv, Libsvm, Xrff
- Tags: Machine Learning, Weka
- Archive: download here
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