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: 50


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.


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 !

Write your own review or comment:

make sure you have javascript enabled or clear this field: