Special Issue “Interactive Machine Learning and Visual Data Mining”
Angela Locoro, in collaboration with Giorgio Di Nunzio of the University of Padova, launched this Special Issue on “Interactive Machine Learning and Visual Data Mining”.
Successful machine learning applications require the correct use of the underlying training data in order to optimize and select the best models for a particular task. During this process, human feedback can correct model errors and update model parameters to dynamically adapt to changing data. Interactive Machine Learning (IML) deals with this Special Issue by creating an efficient collaboration between users and machine learning algorithms.
In this field, Technology-assisted review (TAR) systems and eDiscovery use a kind of human-in-the-loop approach where classification and/or ranking algorithms are continuously trained according to the relevant feedback from expert reviewers until a substantial number of the relevant objects are identified.
Methods to combine (inter)-active machine learning and Visual Data Mining (VDM) interaction approaches through the iterative process with a human-in-the-loop strategy are part of the research questions addressed in this Special Issue.
Topics for this Special Issue are (but are not limited to):
- Design and implementation of interactive machine learning/data mining systems;
- Evaluation approaches/measures of IML and VDM systems;
- User studies and Evaluation protocols;
- Active Learning strategies for IML and VDM;
- Reproducibility of interactive systems.
Please, find more information at the mdpi Information dedicated webpage.
The Special Issue is now open for submissions.
We wait for your enlightening works!
The Guest Editors
Dr. Angela Locoro
Dr. Giorgio Maria Di Nunzio