Automated feature engineering for machine learning models

Abstract

Training computer models by generating time-aware training datasets is provided. A system receives a secondary dataset to be combined with a primary dataset for generation of a training dataset. The primary dataset includes a plurality of data records where at least one data record corresponds to a time-of-prediction value corresponding to a timestamp at which at least one data record was used to generate a prediction. The secondary dataset includes a plurality of features where at least one feature corresponds to a timestamp value. The system selects a feature within the secondary dataset with a timestamp that precedes or matches a time-of-prediction value for a corresponding data record within the primary dataset. The system generates the training dataset that includes the primary dataset and the selected feature. The system trains a model using the generated training dataset.