Abstract: One or more embodiments include a computer-implemented method that includes receiving a data set generated by a machine learning model, wherein the data set comprises a plurality of data samples that are independent of each other, performing two or more fitting operations to fit the data set to a regularized maximum likelihood estimators (MLEs), determining a variance associated with the data set based on a derivative associated with the regularized MLEs, and performing one or more operations associated with the machine learning model based on the variance.