Over a million developers have joined DZone.
{{announcement.body}}
{{announcement.title}}

Predicting Outcomes of Tennis Matches with Dynamic Bayesian Networks

DZone's Guide to

Predicting Outcomes of Tennis Matches with Dynamic Bayesian Networks

· Big Data Zone ·
Free Resource

The open source HPCC Systems platform is a proven, easy to use solution for managing data at scale. Visit our Easy Guide to learn more about this completely free platform, test drive some code in the online Playground, and get started today.

For the purpose of building prediction models in tennis markets, I've developed a Bayesian inference engine in Scala. One of tutorials I wrote on this tool is dedicated to predicting outcomes of tennis matches with Dynamic Bayesian Networks and Expectation Maximization techniques.

Bayes-Scala Project Home Page

Getting Started - Learning parameters with Expectation Maximisation in Unrolled Dynamic Bayesian Networks from incomplete data

Currently I'm evaluating this prediction model on a real data set of tennis matches for last 5 years and I will publish prediction results later on.

Managing data at scale doesn’t have to be hard. Find out how the completely free, open source HPCC Systems platform makes it easier to update, easier to program, easier to integrate data, and easier to manage clusters. Download and get started today.

Topics:

Published at DZone with permission of

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}