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Python3 wrapper for the Weka Machine Learning Workbench

Project Description

The python-weka-wrapper3 package makes it easy to run Weka algorithms and filters from within Python. It offers access to Weka API using thin wrappers around JNI calls using the javabridge package.

Changelog

0.1.2 (2017-01-04)

  • typeconv.double_matrix_to_ndarray no longer assumes a square matrix (https://github.com/fracpete/python-weka-wrapper3/issues/4)
  • len(Instances) now returns the number of rows in the dataset (module weka.core.dataset)
  • added method insert_attribute to the Instances class
  • added class method create_relational to the Attribute class
  • upgraded Weka to 3.9.1

0.1.1 (2016-10-19)

  • plot_learning_curve method of module weka.plot.classifiers now accepts a list of test sets; * is index of test set in label template string
  • added missing_value() methods to weka.core.dataset module and Instance class
  • output variable y for convenience method create_instances_from_lists in module weka.core.dataset is now optional
  • added convenience method create_instances_from_matrices to weka.core.dataset module to easily create an Instances object from numpy matrices (x and y)

0.1.0 (2016-05-09)

  • initial release of Python3 port
Release History

Release History

This version
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0.1.2

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0.1.1

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0.1.0

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