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

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

Open Access
|Aug 2016

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.
DOI: https://doi.org/10.5334/jors.108 | Journal eISSN: 2049-9647
Language: English
Submitted on: Dec 9, 2015
Accepted on: Jul 1, 2016
Published on: Aug 8, 2016
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2016 Christopher Beckham, Mark Hall, Eibe Frank, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.