A Case for Guided Machine Learning - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2019

A Case for Guided Machine Learning


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.
Fichier principal
Vignette du fichier
485369_1_En_22_Chapter.pdf (184.58 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-02520045 , version 1 (26-03-2020)





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⟩
76 View
67 Download



Gmail Facebook Twitter LinkedIn More