Description
Amputation is the opposite of imputation; it is the creation of a missing data mask for complete datasets. Amputation is useful for evaluating the effect of missing values on the outcome of a statistical or machine learning model. In this talk, we present pyampute: the first open-source Python library for data amputation. Our package is compatible with the scikit-learn-style fit and transform paradigm, which allows for seamless integration of amputation in a larger, more complex data processing pipeline.