working-joss.md

title	ML-SIM
tags	Python machine learning evaluation simulation
authors	name orcid affiliation Sarah M Brown 0000-0003-0872-7098 1
affiliations	name index Brown University 1
date	July 2019
bibliography	paper.bib

Summary

Machine learning evaluation is of critical importance

ML sim allows for resampling of a provided dataset according to a causal dag or an inferred bn, or generation of completely synthetic data

Mathematics

Single dollars ($) are required for inline mathematics e.g. $f(x) = e^{\pi/x}$

Double dollars make self-standing equations:

$$\Theta(x) = \left{\begin{array}{l} 0\textrm{ if } x < 0\cr 1\textrm{ else} \end{array}\right.$$

Citations

Citations to entries in paper.bib should be in rMarkdown format.

Figures

Figures can be included like this:

Acknowledgements

We acknowledge contributions from Brigitta Sipocz, Syrtis Major, and Semyeong Oh, and support from Kathryn Johnston during the genesis of this project.

References