Project details for python weka wrapper

Screenshot python weka wrapper 0.1.13

by fracpete - November 1, 2014, 09:59:54 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. 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 "get_class" method to "weka.core.utils" which returns the Python class object associated with the classname in dot-notation
  • "from_commandline" method in "weka.core.utils" now takes an optional "classname" argument, which is the classname (in dot-notation) of the wrapper class to return - instead of the generic "OptionHandler"
  • added "Kernel" and "KernelClassifier" convenience classes to better handle kernel based classifiers
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
0.1.13
  • added "get_class" method to "weka.core.utils" which returns the Python class object associated with the classname in dot-notation
  • "from_commandline" method in "weka.core.utils" now takes an optional "classname" argument, which is the classname (in dot-notation) of the wrapper class to return - instead of the generic "OptionHandler"
  • added "Kernel" and "KernelClassifier" convenience classes to better handle kernel based classifiers
November 1, 2014, 09:59:54
0.1.12
  • added "create_string" class method to the "Attribute" class for creating a string attribute
  • ROC/PRC curves can now consist of multiple plots (ie multiple class labels)
  • switched command-line option handling from "getopt" to "argparse"
  • fixed Instance.get_dataset(self) method
  • added iterators for: rows/attributes in dataset, values in dataset row
  • incremental loaders can be iterated now
October 17, 2014, 00:16:26
0.1.11
  • moved wekaexamples module to separate github project: https://github.com/fracpete/python-weka-wrapper-examples
  • added "stratify", "train_cv" and "test_cv" methods to the Instances class
  • fixed "to_summary" method of the Evaluation class: failed when providing a custom title
September 25, 2014, 00:39:02
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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