Crime Prediction
Named after the Norse God of Foresight, our Crime Prediction model takes in LSOA time series data and gives a propensity at a certain time for these crimes.
Available now (Q2 2019)
product description
The prediction model is accessed through a RESTful JSON API. Additional data is uploaded as a CSV file.
Our Crime Prediction model uses time series data mapped to LSOA (Lower Layer Super Output Area) boundaries.

Predictive models that use lots of past historic data, to train complex algorithms such as neural networks or deep learning algorithms, can be what is called "over fitted". This essentially means that when unseen data is presented to the predictive model that is outside of the cohort or population of data that the model is trained on, the accuracy of the model rapidly diminishes. A neural network that could offer in excess of 0.85 Gini coefficient on one population could offer a 0.25 or lower Gini with a different population.

By using an unsupervised machine learning algorithm, that is still trained on looking for the anomalies associated with a certain population, but not subject to the bias and overfitting, a more realistic 0.65 or above Gini can be achieved.

We help you build your proprietary models, but our platform is intended to be self service and not require a data scientist.
Predictive Crime product launched
New product release - Heimdall