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Mastering JBoss Drools 6

You're reading from   Mastering JBoss Drools 6 Discover the power of Drools 6 and Business Rules for developing complex scenarios in your applications

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Product type Paperback
Published in Mar 2016
Publisher Packt
ISBN-13 9781783288625
Length 330 pages
Edition 1st Edition
Languages
Tools
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Authors (3):
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Mariano De Maio Mariano De Maio
Author Profile Icon Mariano De Maio
Mariano De Maio
Esteban Aliverti Esteban Aliverti
Author Profile Icon Esteban Aliverti
Esteban Aliverti
Mauricio Salatino Mauricio Salatino
Author Profile Icon Mauricio Salatino
Mauricio Salatino
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Toc

Table of Contents (13) Chapters Close

Preface 1. Rules Declarative Nature 2. Writing and Executing Rules FREE CHAPTER 3. Drools Runtime 4. Improving Our Rule Syntax 5. Understanding KIE Sessions 6. Complex Event Processing 7. Human-Readable Rules 8. Rules' Testing and Troubleshooting 9. Introduction to PHREAK 10. Integrating Rules and Processes 11. Integrating Drools with our Apps Index

PMML


The Predictive Model Markup Language (PMML) is an XML-based language aimed at providing a way to exchange different predictive models, for classification or regression purposes, generated using a data mining or machine learning technique. PMML was originally developed by the Data Mining Group (http://www.dmg.org/) in 1997 and its latest version (4.2.1) dates from May 2014.

Even if PMML itself is not a business-oriented language, it is currently possible to generate PMML documents from a variety of well known applications, such as Knime (https://www.knime.org/), or R language (https://www.r-project.org/).

PMML support in Drools is relatively new. It originally started as an experimental module but, with effect from version 6.1, PMML is a first-class citizen of the Drools ecosystem. PMML standard can be used to encode and interchange classification and regression models, such as neural networks, decision trees, scorecards, and others. By adopting PMML, Drools has gained access to a broader...

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