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Automatically Wrangling Spreadsheets into Machine Learning Data Formats

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Advances in Intelligent Data Analysis XVII (IDA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11191))

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Abstract

To help automate the important pre-processing step in machine learning and data mining, we introduce synth-a-sizer, a tool for semi-automatically wrangling spreadsheets into attribute-value format, so that they can be used by popular machine learning tools, only requiring the user to mark cells belonging to one single example. synth-a-sizer is based on inductive programming principles. We introduce synth-a-sizer’s transformations, search algorithm as well as a heuristic and distance measure for identifying types. We also report on a first experimental evaluation.

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Notes

  1. 1.

    http://www.openrefine.org.

  2. 2.

    https://archive.ics.uci.edu/ml/datasets/.

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Acknowledgement

This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No [694980] SYNTH: Synthesising Inductive Data Models).

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Authors and Affiliations

  1. KU Leuven, Leuven, Belgium

    Gust Verbruggen & Luc De Raedt

Authors
  1. Gust Verbruggen
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  2. Luc De Raedt
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Corresponding author

Correspondence to Gust Verbruggen .

Editor information

Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    Wouter Duivesteijn

  2. Department of Information and Computing Sciences, University Utrecht, Utrecht, The Netherlands

    Arno Siebes

  3. University of Helsinki, Helsinki, Finland

    Antti Ukkonen

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Verbruggen, G., De Raedt, L. (2018). Automatically Wrangling Spreadsheets into Machine Learning Data Formats. In: Duivesteijn, W., Siebes, A., Ukkonen, A. (eds) Advances in Intelligent Data Analysis XVII. IDA 2018. Lecture Notes in Computer Science(), vol 11191. Springer, Cham. https://doi.org/10.1007/978-3-030-01768-2_30

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  • DOI: https://doi.org/10.1007/978-3-030-01768-2_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01767-5

  • Online ISBN: 978-3-030-01768-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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