Going beyond Visualization. Verbalization as Complementary Medium to Explain Machine Learning Models

In this position paper, we argue that a combination of visualization and verbalization techniques is beneficial for creating broad and versatile insights into the structure and decision-making processes of machine learning models. Explainability of machine learning models is emerging as an important area of research. Hence, insights into the inner workings of a trained model allow users and analysts, alike, to understand the models, develop justifications, and gain trust in the systems they inform. Explanations can be generated through different types of media, such as visualization and verbalization. Both are powerful tools that enable model interpretability. However, while their combination is arguably more powerful than each medium separately, they are currently applied and researched independently. To support our position that the combination of the two techniques is beneficial to explain machine learning models, we describe the design space of such a combination and discuss arising research questions, gaps, and opportunities

Speculative execution of similarity queries: Real-time parameter optimization through visual exploration

The parameters of complex analytical models often have an unpredictable influence on the models' results, rendering parameter tuning a non-intuitive task. By concurrently visualizing both the model and its results, visual analytics tackles this issue, supporting the user in understanding the connection between abstract model parameters and model results. We present a visual analytics system enabling result understanding and model refinement on a ranking-based similarity search algorithm. Our system (1) visualizes the results in a projection view, mapping their pair-wise similarity to screen distance, (2) indicates the influence of model parameters on the results, and (3) implements speculative execution to enable real-time iterative refinement on the time-intensive offline similarity search algorithm

South China continental margin signature for sandstones and granites from Palawan, Philippines

We report results of heavy mineral analysis and U-Pb dating of detrital zircons from metasediments and Cenozoic sandstones, and U-Pb dating of zircons from Cenozoic granites of the North Palawan Continental Terrane (NPCT) and the South Palawan Terrane (SPT). The NPCT metasediments are derived mainly from granitic and metamorphic rocks of continental character. They contain zircons that indicate a maximum depositional age of Late Cretaceous and other age populations indicating a South China origin. The sediments were deposited on the South China margin before rifting of the continental margin during opening of the South China Sea. Miocene SPT sandstones contain similar heavy mineral assemblages suggesting sources that included NPCT metasediments, metamorphic basement rocks at the contact between the SPT and the NPCT, South China Sea rift volcanic and/or minor intrusive rocks, and the Palawan ophiolite complex. The SPT sandstones are very similar to Lower Miocene Kudat Formation sandstones of northern Borneo suggesting a short-lived episode of sediment transport from Palawan to Borneo in the Early Miocene following arc-continent collision. U-Pb dating of zircons show the Central Palawan granite is Eocene (42 ± 0.5 Ma). The Capoas granite was intruded during a single pulse, or as two separate pulses, between 13.8 ± 0.2 Ma and 13.5 ± 0.2 Ma. Inherited zircon ages from the Capoas granite imply melting of continental crust derived from the South China margin with a contribution from Cenozoic rift-related and arc material