Supervised machine learning
In the “cluster of six”, we used unsupervised machine learning, to reveal hidden structure in unlabelled data, and analyse the voting patterns of Labour Members of Parliament. In this blog post, we’ll use supervised machine learning to see how well we can predict crime in London. Perhaps not specific crimes. But we can use recorded crime summary data at London borough-level (non-personal aggregated data licensed under the Open Government Licence), with some degree of accuracy, to predict crime counts.
Along the way, we’ll see the pay-off from an exploration of multiple models.
Continue reading “Criminal goings-on in a random forest”
Background to G-Cloud pricing
The Digital Marketplace is helping those transforming public services by making it simpler, clearer and faster for them to buy what they need. G-Cloud focuses on cloud-based services. Since its launch in 2012, it has evolved through multiple iterations, with the current version being G-Cloud 9.
So, the introduction of a set of categories in G-Cloud 9 provided a natural step forward. These offered a level of granularity below the three lots of Cloud Hosting, Software and Support. As a result, buyers are able to find and compare groups of suitable products more easily.
Yet there is plenty of opportunity to further simplify the buyer’s task in future G-Cloud iterations. For example, around price comparison. Continue reading “Could G-Cloud pricing be simplified?”