… or evaluating learning algorithms in machine learning research. Further, current machine
learning approaches do not fully exploit the nature of applied machine learning as a co…

… Machine learning techniques have also … key machine learning techniques that are applicable
for smart Cultural Heritage spaces and determine their adherence with the Human-Centred …

… Human-centred, more-than-metric featureselection … , innovative HCAD approach to machine
learning. This flexible and … The design of machine learning algorithms to the uses in which …

… identify opportunities for machine learning to support diabetes … knowledge and rejected
machine learning based decision … suggestions on how machine learning and other artificial …

… This work presents a human-centred thinking approach to applying IML methods. This
guide is intended to be used by AI practitioners who incorporate human factors in their work. …

… were processed and a machine learning algorithm, SegNet, … Another machine learning
algorithm, ie an artificial neural … to the development of human-centred planning and design by …

… The need to solve these issues has evolved into the field of Human-Centered Machine Learning
… area investigating the methods of aligning machine learning systems with human goals, …

… experts, who have in-depth knowledge of machine learning methods but may have limited
knowledge of the application domain. We propose that humancentred machine learning is …

… of machine learning algorithms in predicting building energy consumption. Therefore, this
study proposed an agent-based machine learning … features for machine learning algorithms for …

… of human-centred design developed in other, related fields that can be adopted and adapted
to support the development of human-centred learning … , to define human-centred design in …