deep-significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks
Abstract
A package is provided to facilitate statistical significance testing in ML and DL research, ensuring that reported improvements are not due to statistical chance.
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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