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deep-significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks

Research Output:
Contribution to conference - NOT published in proceeding or journal
Paper
Peer-review

Open access

Publication Information

Output type

Research Output:
Contribution to conference - NOT published in proceeding or journal
Paper
Peer-review

Original language

English

Publication milestones

  • Published - 29/04/2022

Publication status

Published - 29/04/2022

Abstract

A lot of Machine Learning (ML) and Deep Learning (DL) research is of an empirical nature. Nevertheless, statistical significance testing (SST) is still not widely used. This endangers true progress, as seeming improvements over a baseline might be statistical flukes, leading follow-up research astray while wasting human and computational resources. Here, we provide an easy-to-use package containing different significance tests and utility functions specifically tailored towards research needs and usability.

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