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. However, it does not provide any graphical frontend.

Changes to previous version:

• added CostMatrix support in the classifier evaluation
• fixed various retrievals of double arrays (accessed them incorrectly as float arrays), like distributionForInstance for a classifier
• Instances object can now retrieve all (internal) values of an attribute/column as numpy array
• added plotting of cluster assignments to weka.plot.clusterers
• fixed weka.core.utils.from_commandline method
• fixed weka.classifiers.PredictionOutput (get/set_header methods)
• predictions can be turned into an Instances object now using weka.classifiers.predictions_to_instances

BibTeX Entry: Download

Supported Operating Systems: Agnostic

Data Formats: Arff, Csv, Libsvm, Xrff

Tags: Machine Learning, Weka

Archive: download here

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