A Case for Guided Machine Learning
| Autor: | Florian Westphal, Niklas Lavesson, Håkan Grahn |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
interactive machine learning
Computer Sciences Computer science business.industry Process (engineering) Ranging Human Computer Interaction Människa-datorinteraktion (interaktionsdesign) Machine learning computer.software_genre human-in-the-loop Personalization Term (time) Datavetenskap (datalogi) definition Position paper Human-in-the-loop Artificial intelligence business computer guided machine learning |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783030297251 CD-MAKE |
| DOI: | 10.1007/978-3-030-29726-8_22 |
| Popis: | 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. open access |
| Databáze: | OpenAIRE |
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