Last 6 months

Efesto refactoring – technical details

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This post is meant as a description of the APIs and other technical details of the Efesto framework. It continues the introduction made in the previous one. Base concepts. There are some concepts around which the APIs are implemented: Generated resource Unique identifier Context of execution The framework provides and manage default implementations of theRead more →

Efesto refactoring – Introduction

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This post is meant as an introduction of the overall motivations, goals and choices around the Efesto initiative. Premise Originally, "Drools" (and its repository) was meant only as a "rule engine", and all the code was built around this paradigm. Over the years, new engines have been created that used, more or less, the "ruleRead more →

Shopping recommendations in PMML – Kogito at Work

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In a previous post (Shopping recommendations in PMML) we built the main infrastructure for making personalized shopping recommendations depending on the customer shopping history. The companion project was meant to demonstrate a standalone implementation of the Trusty-PMML engine. In this post, we will show how to invoke the engine on a remote Kogito instance. KogitoRead more →

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Shopping recommendations in PMML.

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In previous posts (PMML revisited and Predictions in Kogito) we had a glance at how a PMML engine has been implemented inside Drools/Kogito ecosystem.This time we will start looking at a concrete example of a recommendation engine based on top of PMML.The first part of this post will deal with the ML aspect of it,Read more →

A Genetic Algorithm with Trusty PMML

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Recently, I’ve stumbled upon this interesting article and paired project about a Genetic Algorithm. Then, I’ve asked myself if somehow the features of Trusty PMML could be meaningfully used inside such context. I won’t go deep into technical details, but basically, the Genetic Algorithm classifies features as "genes", a set of genes is a "genoma",Read more →

Predictions in Kogito: PMML endpoints with OpenAPI

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Introduction PMML is an XML standard whose scope is to define different kinds of predictive models (Regression, Scorecard, Tree, Neural Network, etc) in a system-agnostic way, so that it may be used and shared by different systems/implementations. The OpenAPI Specification (OAS) defines a standard, language-agnostic interface to RESTful APIs which allows both humans and computersRead more →

PMML revisited

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Hi folks! The beginning of this year brings with it the initiative to re-design the Drools PMML module. In this post I will describe how we are going to approach it, what’s the current status, ideas for future development, etc. etc so… stay tuned! Background PMML is a standard whose aim is to "provide aRead more →