Machine learning generates insights into worldwide terrorist attacks

A team of researchers has used machine learning to predict and explain terrorist attacks. Their tests suggest the models can accurately predict attacks in regions that are already affected by terrorism. However, they found that “black swan events,” which occur sporadically, are almost impossible to predict. The researchers, led by Dr Andre Python from Zhejiang University in China, used publicly available data to analyze the location and data of attacks