ImputeViz: A Visual Analytics Dashboard for Diagnosing Missing Data and Comparing Imputation Methods
Missing data is a persistent obstacle in scientific, social science, and public health research, often biasing analyses and placing accountability on analysts for how they handle missing values. We introduce ImputeViz, an integrated visual analytics dashboard that supports diagnosing missingness, configuring imputation models, and evaluating results. The system brings together widely used methods, including MICE, Random Forest, XGBoost, and kNN, within an interactive environment that makes missingness patterns explicit. To support geospatial reasoning, we introduce gKNN, a geographically informed kNN variant that blends socioeconomic and spatial distances and exposes donor contributions, ...
| Authors | Aitik Dandapat, Lalith Punepalle Raveendrareddy, Mithilesh Kumar Singh et al. |
|---|---|
| Primary category | cs.HC |
| Published | 9 July 2026 |
| Last updated at source | 9 July 2026 |
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