Multi-Target Prediction with Trees and Tree Ensembles

author: Sašo Džeroski, Department of Intelligent Systems, Jožef Stefan Institute
published: June 28, 2019,   recorded: May 2019,   views: 60
Categories

Slides

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

Increasingly often, we need to learn predictive models from big or complex data, which may comprise many examples and many input/output dimensions. When more than one target variable has to be predicted, we talk about multi-target prediction. Predictive modeling problems may also be complex in other ways, e.g., they may involve incompletely/partially labelled data, as in semi-supervised learning, or data placed in a network context. The talk will first give an introduction to the different tasks of multi-target prediction, such as multi-target classification and regression, hierarchical versions thereof, and versions of the tasks that involve additional complexity (such as semi-supervised multi-target regression and network-based hierarchical multi-label classification). It will continue to present methods for solving such tasks, in particular predictive clustering trees and ensembles thereof. Finally, it will present example applications of multi-target prediction in the life sciences, focusing on predictive modeling in virtual compound screening for drug repurposing.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Reviews and comments:

Comment1 fredluis, October 9, 2019 at 7:26 a.m.:

There is a lot of new information coming to light and it would be useful if you could give some updates since your opinion is so valued. https://www.montgomerytreecare.com


Comment2 Claire Smith, November 22, 2019 at 3:03 a.m.:

regression trees, tree ensembles random forests, bagging and ... and in particular their instantiation for predicting multiple targets. https://www.bathroomrenovationscentra...


Comment3 Silver Reyes, December 6, 2019 at 5:03 p.m.:

https://www.bathroomrenovationssunshi... which combine tree models and linear functions. ... multi-target prediction, rule learning, and rule ensembles


Comment4 Jason Smith, January 6, 2020 at 5:43 a.m.:

In this work, we address the task of feature ranking for multi-target regression (MTR). The task of MTR concerns problems where there are multiple continuous dependent variables and the goal is to learn a model for predicting all of the targets simultaneously. https://www.bathroomremodelminneapoli...


Comment5 Reynaldo Oliveros, January 13, 2020 at 11:02 a.m.:

They are more accurate than, for instance, multi-target regression trees, but not quite as accurate as multi-target random forests.
https://www.deckbuildersomahane.com/


Comment6 Fancypants, February 6, 2020 at 3:24 a.m.:

The prediction task is called multi-target prediction and it can be considered as a generalization of multi-label classification or multi-target regression. https://northshoregasfitters.info/

Write your own review or comment:

make sure you have javascript enabled or clear this field: