Visual Analytics for Interactive Machine Learning - A Modular Multi-View Approach

Interactive machine learning enhances data pre-processing, feature engineering, and modeling through human interactions. As interactive machine learning becomes more in-corporated into visual analytics, new pipelines, concepts, and task taxonomies rise. A common technique for managing complexity in visual analytic systems is multiple-linked views. By now no comprehensive concept exists for multiple-linked views across all stages of the visual analytic pipeline. Therefore, we introduce a conceptual model that shows the possible interactions between humans and computers at each step of the VA pipeline. Our main contribution is a coordination model for linking multiple views across each layer of the VA pipeline.