Project details for python weka wrapper

Screenshot python weka wrapper 0.1.0

by fracpete - April 28, 2014, 23:18:48 CET [ Project Homepage BibTeX Download ]

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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. However, it does not provide any graphical frontend at this stage.

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download
URL: Project Homepage
Supported Operating Systems: Agnostic
Data Formats: Arff, Csv, Libsvm, Xrff
Tags: Machine Learning, Weka
Archive: download here

Other available revisons

Version Changelog Date
0.1.10
  • fixed adding custom classpath using jvm.start(class_path=[...])
August 29, 2014, 05:00:14
0.1.9
  • added static methods to Instances class: summary, merge_instances, append_instances
  • added methods to Instances class: delete_with_missing, equal_headers
August 29, 2014, 04:58:45
0.1.8
  • fixed installer: MANIFEST.in now includes CHANGES.rst and DESCRIPTION.rst as well
June 26, 2014, 02:38:12
0.1.7
  • fixed weka/plot/dataset.py imports to avoid error when testing for matplotlib availability
  • Instance.create_instance (weka/core/dataset.py) now accepts Python list and Numpy array
June 26, 2014, 02:14:16
0.1.6
  • added troubleshooting section for Mac OSX to documentation
  • recompiled helper jars with 1.6 rather than 1.7
  • added link to Google Group
May 29, 2014, 06:02:41
0.1.5
  • 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
May 23, 2014, 06:40:42
0.1.4
  • dependencies for plotting are now optional (pygraphviz, PIL, matplotlib)
  • plots now support custom titles
May 19, 2014, 03:02:32
0.1.3
  • improved documentation
  • added PRC curve plot
  • aligned to PEP8 style guidelines
  • fixed variety of little bugs (not so commonly used methods)
  • fixed lib directory reference in make files for Java helper classes
May 17, 2014, 13:37:54
0.1.2
  • added matrix plot
  • added scatter plot for two attributes
  • fixes in constructors of classes
  • added MultiFilter convenience class
  • predictions (of classifiers) can now be collected and output using the PredictionOutput class
  • added support for attribute statistics
May 13, 2014, 07:11:07
0.1.1
  • constructors now take list of commandline options as well
  • added Weka package support (list/install/uninstall)
  • ROC plotting for classifiers
  • improved code documentation
  • added more examples
  • added more datasets
  • using javabridge 1.0.1 now
May 2, 2014, 03:35:38
0.1.0

Initial Announcement on mloss.org.

April 28, 2014, 23:18:48

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