Release v0.1.7

• 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

Release v0.1.6

• added troubleshooting section for Mac OSX to documentation
• recompiled helper jars with 1.6 rather than 1.7 to make it work on Mac OSX
• added link to Google Group

Release v0.1.5

• 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

Release v0.1.4

• dependencies for plotting are now optional (pygraphviz, PIL, matplotlib)
• plots now support custom titles

Release v0.1.3

• 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

Release v0.1.2

• 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

Release 0.1.1

Changes

• 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

Release 0.1.0

Initial release of Python wrapper for Weka, no GUI.