Abstract : Involving humans in the learning process of a machine learning algorithm can have many advantages ranging from establishing trust into a particular model to added personalization capabilities to reducing labeling efforts. While these approaches are commonly summarized under the term interactive machine learning (iML), no unambiguous definition of iML exists to clearly define this area of research. In this position paper, we discuss the shortcomings of current definitions of iML and propose and define the term guided machine learning (gML) as an alternative.
https://hal.inria.fr/hal-02520045 Contributor : Hal IfipConnect in order to contact the contributor Submitted on : Thursday, March 26, 2020 - 1:49:39 PM Last modification on : Tuesday, March 31, 2020 - 3:50:37 PM Long-term archiving on: : Saturday, June 27, 2020 - 2:41:35 PM
Florian Westphal, Niklas Lavesson, Håkan Grahn. A Case for Guided Machine Learning. 3rd International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE), Aug 2019, Canterbury, United Kingdom. pp.353-361, ⟨10.1007/978-3-030-29726-8_22⟩. ⟨hal-02520045⟩