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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.
- Changes to previous version:
- added unit testing framework
- added method "refresh_cache()" to "weka/core/packages.py" to allow user to refresh local cache
- method "get_classname" in "weka.core.utils" now handles Python objects and class objects as well
- added convenience method "get_jclass" to "weka.core.utils" to instantiate a Java class
- added a "JavaArray" wrapper for "arrays, which allows getting/setting elements and iterating
- added property "classname" to class "JavaObject" for easy access to classname of underlying object
- added class method "parse_matlab" for parsing Matlab matrix strings to "CostMatrix" class
- "predictions" method of "Evaluation" class now return "None" if predictions are discarded
- "Associator.get_capabilities()" method is now a property: "Associator.capabilities"
- added wrapper classes for Java enums: "weka.core.classes.Enum"
- fixed retrieval of "sumSq" in "Stats" class (used by "AttributeStats")
- fixed "cluster_instance" method in "Clusterer" class
- fixed "filter" and "clusterer" properties in clusterer classes ("SingleClustererEnhancer", "FilteredClusterer")
- added "crossvalidate_model" method to "ClusterEvaluation"
- added "get_prc" method to "plot/classifiers.py" for calculating the area under the precision-recall curve
- "Filter.filter" method now handles list of "Instances" objects as well, applying the filter sequentially to all the datasets (allows generation of compatible train/test sets)
- BibTeX Entry: Download
- Supported Operating Systems: Agnostic
- Data Formats: Arff, Csv, Libsvm, Xrff
- Tags: Machine Learning, Weka
- Archive: download here
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