python-weka-wrapper 0.2.1 released

With the unit testing framework finally in place (and fixing a number of bugs), I’ve made a new release available.

Here is the list of all the changes:

  • added unit testing framework
  • added method refresh_cache() to weka/core/ to allow user to refresh local cache
  • method get_classname in weka.core.utils now handles Python objects and class objects as well
  • added convenience method get_jclass to weka.core.utils to instantiate a Java class
  • added a JavaArray wrapper for arrays, which allows getting/setting elements and iterating
  • added property classname to class JavaObject for easy access to classname of underlying object
  • added class method parse_matlab for parsing Matlab matrix strings to CostMatrix class
  • predictions method of Evaluation class now return None if predictions are discarded
  • Associator.get_capabilities() method is now a property: Associator.capabilities
  • added wrapper classes for Java enums: weka.core.classes.Enum
  • fixed retrieval of sumSq in Stats class (used by AttributeStats)
  • fixed cluster_instance method in Clusterer class
  • fixed filter and clusterer properties in clusterer classes (SingleClustererEnhancer, FilteredClusterer)
  • added crossvalidate_model method to ClusterEvaluation
  • added get_prc method to plot/ for calculating the area under the precision-recall curve
  • Filter.filter method now handles list of Instances objects as well, applying the filter sequentially to all the datasets (allows generation of compatible train/test sets)

NB: I’ve flagged the library now as beta as well.