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DOE OSTI · 1841525

Machine Learning for Correlated Intelligence. LDRD SAND Report

Moore, Emily R.·Proudfoot, Oliver S.·Qiu, Henry·Ganter, Tyler·Lemon, Brandon·Pitts, Christopher W.·Pitts, Todd A.·Moon, Todd K.
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Abstract

The Machine Learning for Correlated Intelligence Laboratory Directed Research & Development (LDRD) Project explored competing a variety of machine learning (ML) classification techniques against a known, open source dataset through the use of a rapid and automated algorithm research & development (RD) infrastructure. This approach relied heavily on creating an infrastructure in which to provide a pipeline for automatic target recognition (ATR) ML algorithm competition. Results are presented for nine ML classifiers against a primary dataset using the pipeline infrastructure developed for this project. New approaches to feature set extraction are presented and discussed as well.

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Moore, Emily R., Proudfoot, Oliver S., Qiu, Henry, Ganter, Tyler, Lemon, Brandon, Pitts, Christopher W., Pitts, Todd A., Moon, Todd K.. 2022-01-22. Machine Learning for Correlated Intelligence. LDRD SAND Report. https://doi.org/10.2172/1841525

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