Augustus is a scalable Python-based open source system for building and scoring statistical and data mining models. Augustus follows the PMML standard so that models can be easily imported and exported as PMML files.
Augustus 0.5.x was a rewrite of the PMML-compliant scoring engine with two important changes:
- Augustus now has the ability to build models in batch mode using static data files as usual, but also in a streaming mode in which data is read only once.
- Augustus now supports custom processing, a mechanism that allows the user to embed arbitrary Python code inside of Augustus. This provides a simple mechanism, for example, to combine multiple models and produce a single score.
Augustus 0.5.x uses the latest PMML specification 4.1 from December of 2011.
The latest version, Augustus 0.5.2.0, was released on April 4, 2012. Its model coverage is: Tree, Regression, Baseline, Rule Set, Naïve-Bayes, and Cluster.
AdReady is an Open Data Group Business Partner and is using the latest Augustus for the development and deployment of sophisticated statistical models for use in a large, robust, and scalable targeted ad-bidding system. AdReady’s Real-Time-Bidding (RTB) enables advertisers to bid more effectively on precise inventory and audience targets. Bid requests need to be collected, scored against segmented models, and responded to in less than 100 ms.
By using Augustus, AdReady can grow using elastic capacity and score on VM instances, bypassing the normal (Augustus) data pipeline and send events directly into the scoring engine processing loop from their Python MVC web framework (Django over Apache). AdReady described their use of Augustus in a nice blog post today.
To learn more about building a scalable analytics platform using Augustus, please contact us at info at opendatagroup.com.