Crime prediction using machine learning. The web application is the final output of the London Crime Prediction blogpost based on open data. Predictions are done at the LSOA (layer super output areas) Level for 2017.

London crime prediction (2017)

The layers:

1. Residuals: difference between the prediction and the number of crimes in 2016. It gives a good overview of the predictive model accuracy and the areas where it's (relatively) less performant. The predictive model supporting these data got a 0.92 R2 score which is very good.

2. Clustering layer, this is a description of the crime type patterns per LSOA over the 4 last years (2013-2016). Outliers are LSOA with a large value of crime over the average regarding some type of crime.

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Alex E

“Maps are like campfires – everyone gathers around them, because they allow people to understand complex issues at a glance, and find agreement about how to help the land.”