Improving Meta-learning for Algorithm Selection by Using Multi-label Classification: A Case of Study with Educational Data Sets
Recommending classification algorithms is an open research problem the solution to which is of tremendous value for practitioners and non-experts data mining users such as educators. This paper proposes a new meta-learning framework for educational domains based on the use of multi-label learning fo...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Atlantis Press
2015-12-01
|
Series: | International Journal of Computational Intelligence Systems |
Subjects: | |
Online Access: | https://www.atlantis-press.com/article/25868655.pdf |