Multi-target prediction (multitarget)

Multi-target prediction tries to achieve better prediction accuracy or speed through prediction of multiple dependent variables at once. It works on multi-target data, which is also supported by Orange’s tab file format using multiclass directive.

List of supported learners:

• <no title>
• Examples
• Examples
• Neural Network Learner (neural)
• PLS Regression Learner

Additionally orangecontrib.earth.EarthLearner from the orangecontrib.earth package is also supports multi-target predictions.

For evaluation of multi-target methods, see the corresponding section in Examples.

The addon also includes three sample datasets:

• bridges.tab - dataset with 5 multi-class class variables
• flare.tab - dataset with 3 multi-class class variables
• emotions.tab - dataset with 6 binary class variables (a multi-label dataset)

Example of loading an included dataset:

import Orange
data = Orange.data.Table('multitarget:bridges.tab')