Experimental Design for Bathymetry Editing

Julaiti Alafate; Yoav Freund; David T. Sandwell; Brook Tozer

Experimental Design for Bathymetry Editing

Machine Learning 2020-07-16 v1 Machine Learning

Authors: Julaiti Alafate , Yoav Freund , David T. Sandwell , Brook Tozer

Abstract

We describe an application of machine learning to a real-world computer assisted labeling task. Our experimental results expose significant deviations from the IID assumption commonly used in machine learning. These results suggest that the common random split of all data into training and testing can often lead to poor performance.

Keywords

machine learning human-computer interaction

Cite

@article{arxiv.2007.07495,
  title  = {Experimental Design for Bathymetry Editing},
  author = {Julaiti Alafate and Yoav Freund and David T. Sandwell and Brook Tozer},
  journal= {arXiv preprint arXiv:2007.07495},
  year   = {2020}
}

Comments

Published as a workshop paper at ICML 2020 Workshop on Real World Experiment Design and Active Learning

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