EAN: 9783319904023

HUMAN-COMPUTER INTERACTION SERIES HUMAN AND M...

With an evolutionary advancement of Machine Learning (ML) algorithms  a rapid increase of data
volumes and a significant improvement of computation powers  machine learning becomes hot in
different applications. However  because of the nature of ¿black-box¿ in ML methods  ML still
needs to be interpreted to link human and machine learning for transparency and user acceptance
of delivered solutions. This edited book addresses such links from the perspectives of
visualisation  explanation  trustworthiness and transparency. The book establishes the link
between human and machine learning by exploring transparency in machine learning  visual
explanation of ML processes  algorithmic explanation of ML models  human cognitive responses in
ML-based decision making  human evaluation of machine learning and domain knowledge in
transparent ML applications. This is the first book of its kind to systematically understand
the current active research activities and outcomes related to human and machine learning. The
book will not only inspire researchers to passionately develop new algorithms incorporating
human for human-centred ML algorithms  resulting in the overall advancement of ML  but also
help ML practitioners proactively use ML outputs for informative and trustworthy decision
making. This book is intended for researchers and practitioners involved with machine learning
and its applications. The book will especially benefit researchers in areas like artificial
intelligence  decision support systems and human-computer interaction.

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