METHOD AND SYSTEM FOR ADAPTIVELY IMPUTING SPARSE AND MISSING DATA FOR PREDICTIVE MODELS

摘要

Described is an approach that provides an adaptive solution to missing data for machine learning systems. A gradient solution is provided that is attentive to imputation needs at each of several missingness levels. This multilevel approach treats data missingness at any of multiple severity levels while utilizing, as much as possible, the actual observed data.