Machine learning – and Apache Mahout

Isabel Drost recently contributed some enhancements to the Guided Editor (to allow nested facts, very handy) – quite a clever patch. As if that isn’t enough, she is also a contributor to the Apache Mahout project:Mahout is: (in the projects own words): “Mahout’s goal is to build scalable, Apache licensed machine learning libraries.” The projectRead more →

Drools and Machine Learning

I’m Gizil. I am doing my master thesis in Drools project. I’m working on decision trees. I have made an ID3, C4.5 implementation with rule generation. I’m investigating bagging and boosting algorithm in order to produce better rules. I am using Annotations on object fields to be able to process extra information on the attributes ofRead more →

Zementis Drools Case Study

Here at Zementis we have developed a decision engine called ADAPA – Adaptive Decision and Predictive Analytics (http://zementis.com/products.htm) that offers at its core batch and real-time scoring of predictive models as well as fast execution of business rules. As you readers might have guessed, the rules engine is Drools. I will briefly sketch the coreRead more →