System and method to improve accuracy of regression models trained with imbalanced data

Abstract

A method for training a machine learning model includes: receiving, by a computer system including a processor and memory, a training data set including imbalanced data; computing, by the computer system, a label density f(x) in the training data set, computing, by the computer system, a weight function w(x) including a term that is inversely proportional to the label density; weighting, by the computer system, a loss function(x, {circumflex over (x)}) in accordance with the weight function to generate a weighted loss function(x, {circumflex over (x)}); training, by the computer system, a continuous machine learning model in accordance with the training data set and the weighted loss function(x, {circumflex over (x)}); and outputting, by the computer system, the trained continuous machine learning model.