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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:
- 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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