Thèse
Collaborative interactive machine learning : Co-constructing trustworthy predictive models to improve wheat quality assessments
In interactive machine learning, humans and machine learning algorithms collaborate to achieve tasks mediated by interactive visual interfaces. In traditional interactive machine learning, models are often developed with single users in mind. However, real world applications often require the collaboration of different types and levels of expertise to help reliably develop and assess the results of machine learning models.