Facets is a set of interactive software tools for the statistical analysis, distribution visualization, and multidimensional exploration of machine learning datasets. It provides a visual interface for identifying outliers and missing values in numeric and string data, specifically designed for auditing dataset quality and identifying skews between training and validation sets.
The system uses multidimensional facet-based visualization and interactive bucketing to map individual data points across multiple feature axes. It employs synchronized view filtering and animated dimension transitions to maintain visual context while navigating large datasets to detect systematic classifier failures and model errors.
The toolkit covers dataset distribution auditing and feature-by-feature statistical analysis. It enables the detection of distribution skews and the exploration of data points through coordinated filtering and client-side statistical aggregation.
