Just published a new release of the python-weka-wrapper library on PyPi. This release includes a number of bugfixes, mainly encountered when creating scripts for the MOOC series Data Mining with Weka. Here’s a short overview:
- 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