SaaS Rule Learner

No alt text provided for this imageFinally, our SaaS Rule Learner became publicly available allowing business analysts to extract business rules from their historical data sets. They can do it without any downloads directly from Amazon cloud using AWS Marketplace SaaS subscription – see Watch this video that describes how to use it for the demo and custom data sets. Try SaaS Rule Learner from

SaaS Rule Learner is a cloud-based tool for subject matter experts who want to apply Machine Learning (ML) to generate business rules from their historical data without necessity to install and configure any software. No installation, no configuration, no preliminary knowledge of ML, statistics, data science, or programming is required.

You can start playing with demo models that consist of one Excel file with two simple tables for training instances and a glossary. Training instances can have many attributes with the last one being a Class attribute, which values are already known. Examples of demo models are described at Rule Learner will generate business rules capable to find the values of the class attribute for new instances.

You can open and look at the selected Excel file, choose one of a few ML algorithms (such as RIPPER or C4.5), and with a one-click on “RUN RULE LEARNER” generate business rules capable to classify new instances. It will also show you an average accuracy. There are more accuracy metrics available, and together with the generated rules they can be downloaded as one Excel file “GeneratedRules.xls”.

Then you can create your own Excel file with your training data. After signing up using your AWS account, you will be able to select or drag&drop your Excel as a “custom” model. Then you will click on “RUN RULE LEARNER” to generate business rules for your data sets. Each rules generation will cost you $0.25 and you will receive a bill from Amazon at the end of the month. You pay only when you actually use Rule Learner for your own data.

Alternatively, you always may install Rule Learner on your own machine – see


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