Better Model Performance Through Algorithmic Diversity

The upcoming release on BigML keeps pushing the envelope for more people to gain access to and make a bigger impact with Machine Learning. This release features a brand new resource providing a novel way to combine models: BigML Fusions.

In this post, we’ll do a quick introduction to Fusions before we move on to the remainder of our series of 6 blog posts (including this one) to give you a detailed perspective of what’s behind this new capability. Today’s post explains the basic concepts that will be followed by an example use case. This will be followed by three more articles focused on how to use Fusions through the BigML Dashboard, API, and WhizzML in an automated fashion. Finally, we will complete this series of posts with a technical view of how Fusions work behind the scenes.

Source de l’article sur DZONE