WekaPyScript: Classification, Regression, and Filter Schemes for WEKA Implemented in Python. Issue 1 (8th August 2016)

• Record Type: Journal Article
• Authors: Beckham, Christopher; Hall, Mark; Frank, Eibe
• Is Part Of: Journal of open research software. Volume 4:Issue 1(2016)
• Publication Date: 2016-08-08
• Subjects: Python -- WEKA -- machine learning -- data mining; Computer software -- Reusability -- Periodicals; Open source software -- Periodicals; 005
• DOI: 10.5334/jors.108
• Languages: English
• ISSNs: 2049-9647

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.