Machine Learning with Business Rules on IBM Z: Acting on Your Insights

• Author(s): Mike Johnson, Chris Backhouse, Stéphane Faure, David Griffiths, Yann Kindelberger, Ke Wei Wei, Hao Zhang, IBM Redbooks,
• Publisher: IBM Redbooks
• Pages: 42
• ISBN_10: 0738456926
  ISBN_13: 9780738456928
  
• Language: en
• Categories: Computers / General ,

Description:...

This Redpaper introduces the integration between two IBM products that you might like to consider when implementing a modern agile solution on your Z systems. The document briefly introduces Operational Decision Manager on z/OS and Machine learning on z/OS. In the case of Machine Learning we focus on the aspect of real-time scoring models and how these can be used with Business Rules to give better decisions.

Note: Important changes since this document was written:
This document was written for an older release of Operational Decision Manager for z/OS (ODM for z/OS). ODM for z/OS 8.9.1 required the writing of custom Java code to access a Watson Machine Learning for z/OS Scoring Service (this can be seen in ). Since that time ODM for z/OS version 8.10.1 has been released and much improves the integration experience. Integrating the two products no longer requires custom Java code. Using ODM for z/OS 8.10.1 or later you can use an automated wizard in the ODM tooling to:

• Browse and select a model from Watson Machine Learning
  
• Import the Machine Learning data model into your rule project
  
• Automatically generate a template rule that integrates a call to the Watson Machine Learning scoring service
  

Download and read this document for:

• Individual introductions to ODM for z/OS and Machine learning
  
• Discussions on the benefits of using the two technologies together
  
• Information on integrating if you have not yet updated to ODM for z/OS 8.10.1
  

For information about the machine learning integration in ODM for z/OS 8.10.1 see IBM Watson Machine Learning for z/OS integration topic in the ODM for z/OS 8.10.x Knowledge Center

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