AGGREGATING UNIQUE TRAINING DATA

Methods, systems, and computer-readable media that include processes related to training improved machine learning models using aggregated and unique training data. In one example, a process includes identifying a rare event for which a predicted target variable is to be generated, training a naïve machine learning model to generate the predicted target variable using a particular subset of the training data, and determining that a sparsity of training data exists for the rare event in the particular subset of training data. The process also includes the actions of, in response to determining that a sparsity off training data exists for the rare event in the particular subset of the training data, selecting other subsets of the training data, and identifying feature sets that are associated with the rare event from the selected other subsets of the training data.