Predicting Terrorist Attacks in the United States using Localized News Data. (arXiv:2201.04292v1 [cs.LG])

Dozens of terrorist attacks are perpetrated in the United States every year,
often causing fatalities and other significant damage. Toward the end of better
understanding and mitigating these attacks, we present a set of machine
learning models that learn from localized news data in order to predict whether
a terrorist attack will occur on a given calendar date and in a given state.
The best model--a Random Forest that learns from a novel variable-length moving
average representation of the feature …

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