The EM algorithm finds maximum-likelihood estimates for model parameters when you have incomplete data. The "E-Step" finds probabilities for the assignment of data points, based on a set of hypothesized probability density functions; The "M-Step" updates the original hypothesis with new data. The cycle repeats until the parameters stabilize.
Click on the picture to zoom in
DSC Resources
Comment
Thank you for this, it really helped.
Lance Norskog
Posted 1 March 2021
© 2021 TechTarget, Inc.
Powered by
Badges | Report an Issue | Privacy Policy | Terms of Service
Most Popular Content on DSC
To not miss this type of content in the future, subscribe to our newsletter.
Other popular resources
Archives: 2008-2014 | 2015-2016 | 2017-2019 | Book 1 | Book 2 | More
Most popular articles
You need to be a member of Data Science Central to add comments!
Join Data Science Central