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Reproducible Pattern Recognition Research: The Case of Optimistic SSL

Machine Learning 2016-12-28 v1 Machine Learning
Authors: Jesse H. Krijthe , Marco Loog
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Abstract

In this paper, we discuss the approaches we took and trade-offs involved in making a paper on a conceptual topic in pattern recognition research fully reproducible. We discuss our definition of reproducibility, the tools used, how the analysis was set up, show some examples of alternative analyses the code enables and discuss our views on reproducibility.

Keywords

machine learning statistical inference and evidence statistical inference and model selection

Cite

@article{arxiv.1612.08650,
  title  = {Reproducible Pattern Recognition Research: The Case of Optimistic SSL},
  author = {Jesse H. Krijthe and Marco Loog},
  journal= {arXiv preprint arXiv:1612.08650},
  year   = {2016}
}

Comments

Presented at RRPR 2016: 1st Workshop on Reproducible Research in Pattern Recognition

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