-
- Description:
A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls. Offers all major APIs, like data generators, loaders, savers, filters, classifiers, clusterers, attribute selection, associations and experiments. Weka packages can be listed/installed/uninstalled as well. It does not provide any graphical frontend, but some basic plotting and graph visualizations are available through matplotlib and pygraphviz. A simple workflow engine was added with release 0.3.0.
- Changes to previous version:
- added "get_tags" class method to "Tags" class for easier instantiation of Tag arrays
- added "find" method to "Tags" class to locate "Tag" object that matches the string
- fixed "getitem" and "setitem" methods of the "Tags" class
- added "GridSearch" meta-classifier with convenience properties to module "weka.classifiers"
- added "SetupGenerator" and various parameter classes to "weka.core.classes"
- added "MultiSearch" meta-classifier with convenience properties to module "weka.classifiers"
- added "quote"/"unquote" and "backquote"/"unbackquote" methods to "weka.core.classes" module
- added "main" method to "weka.core.classes" for operations on options: join, split, code
- added support for option handling to "weka.core.classes" module
- BibTeX Entry: Download
- Supported Operating Systems: Agnostic
- Data Formats: Arff, Csv, Libsvm, Xrff
- Tags: Machine Learning, Weka
- Archive: download here
Comments
No one has posted any comments yet. Perhaps you'd like to be the first?
Leave a comment
You must be logged in to post comments.