(updated on June 10, 2020)
A multi-output regression task predicts multiple numerical properties for each sample (reference).
The article titled "Regression Models with multiple target variables" by Kiran Karkera (link) covers exactly what I am interested. Here are the key points other than the modeling details.
- Terminology: multi-output regression or multi-target regression; related terms for classification tasks are multi-label classification, multi-class classification, and multioutput-multiclass classification (aka multi-task classification).
- Popular open source ML libraries have little support for the multi-output regression task.
These are the two papers that are mentioned in Kiran Karkera's article.
- Borchani et al. 2015 has a good overview of the model approaches to multi-output regression.
- Kocev et al. 2007 discusses the use of ensembles for multi-objective decision trees.
Here is an article discussing how to develop multi-output regression models with python posted online on March 27, 2020.