Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction

We present the Mind the Gap Model (MGM), an approach for interpretable feature extraction and selection. By placing interpretability criteria directly into the model, we allow for the model to both optimize parameters related to interpretabil-ity and to directly report a global set of distinguishable dimensions to assist with further data exploration and hypothesis generation.