Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training explainable machine learning models are described. An exemplary method includes obtaining, by sampling without replacement for a plurality of times, a plurality of training datasets from a plurality of historical data records, including a first training dataset and a second training dataset with one or more overlapped historical data records; generating a plurality of histograms respectively corresponding to the plurality of training datasets, in which a histogram of the second training dataset reuses one or more data points corresponding to the one or more overlapped historical data records in a histogram of the first training dataset; training, based on the plurality of histograms, one or more machine learning models corresponding to the one or more user features; and providing personalization based on the one or more machine learning models.
SYSTEM AND METHOD FOR EFFICIENTLY TRAINING INTELLIGIBLE MODELS