In this project, a group of students will explore the state of the art on multi-output regression methods. The students should choose at least two regression families such as kernel methods, tree methods, variants of svm regression, etc, identify promising multi-output methodologies and justify their choice in a written report. They will then proceed to implement at least two of them and evaluate them on various data sets


  • Understanding of multi-output methods
  • Implementation in a real-world data set
  • Sharpen development skills in Python

Data sets

  • Private dataset will be shared individually

Target audience

Ideal for students seeking to understand regression methods better and apply the state of the art