WekaPyScript: Classification, Regression, and Filter Schemes for WEKA Implemented in Python

Authors

  • Christopher Beckham Department of Computer Science, The University of Waikato
  • Mark Hall Pentaho Corporation
  • Eibe Frank Department of Computer Science, The University of Waikato

DOI:

https://doi.org/10.5334/jors.108

Keywords:

Python, WEKA, machine learning, data mining

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.

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Published

2016-08-08

Issue

Section

Software Metapapers