python-weka-wrapper3 0.1.3

Python3 wrapper for the Weka Machine Learning Workbench

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

0.1.3 (2017-08-23)

• added check_for_modified_class_attribute method to FilterClassifier class

• added complete_classname method to weka.core.classes module, which allows completion of partial classnames like .J48 to weka.classifiers.trees.J48 if there is a unique match; JavaObject.new_instance and JavaObject.check_type now make use of this functionality, allowing for instantiations like Classifier(cls=”.J48”)

• jvm.start(system_cp=True) no longer fails with a KeyError: ‘CLASSPATH’ if there is no CLASSPATH environment variable defined

• Libraries mtl.jar, core.jar and arpack_combined_all.jar were added as is to the weka.jar in the 3.9.1 release instead of adding their content to it. Repackaged weka.jar to fix this issue (https://github.com/fracpete/python-weka-wrapper3/issues/5)

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