Interactive labelling of a multivariate dataset for supervised machine learning using linked visualisations, clustering, and active learning

• Main Authors: Chegini, Mohammad, Bernard, Jürgen, Berger, Philip, Sourin, Alexei, Andrews, Keith, Schreck, Tobias
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2019
• Subjects: Engineering::Computer science and engineering; Labelling; Clustering
• Online Access: https://hdl.handle.net/10356/86031; http://hdl.handle.net/10220/49845
• Institution: Nanyang Technological University

Supervised machine learning techniques require labelled multivariate training datasets. Many approaches address the issue of unlabelled datasets by tightly coupling machine learning algorithms with interactive visualisations. Using appropriate techniques, analysts can play an active role in a highly...