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arXiv · 2007.07495

Experimental Design for Bathymetry Editing

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

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Julaiti Alafate, Yoav Freund, David T. Sandwell, Brook Tozer. 2020-07-15. Experimental Design for Bathymetry Editing. https://arxiv.org/abs/2007.07495

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