WekaPyScript: Classification, regression, and filter schemes for WEKA implemented in Python
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© 2016 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/
Abstract
WekaPyScript is a package for the machine learning software WEKA that allows learning algorithms and preprocessing methods for classification and regression to be written in Python, as opposed to WEKA’s implementation language, Java. This opens up WEKA to its machine learning and scientific computing ecosystem. Furthermore, due to Python’s minimalist syntax, learning algorithms and preprocessing methods can be prototyped easily and utilised from within WEKA. WekaPyScript works by running a local Python server using the host’s installation of Python; as a result, any libraries installed in the host installation can be leveraged when writing a script for WekaPyScript. Three example scripts (two learning algorithms and one preprocessing method) are presented.
Citation
Beckham, C. J., Hall, M. A., & Frank, E. (2016). WekaPyScript: Classification, regression, and filter schemes for WEKA implemented in Python. Journal of Open Research Software, 4, e33. http://doi.org/10.5334/jors.108