Optimizing lossy compression for nonhomogeneous multivariate black-box classification models

Abstract

A service compresses a data set in accordance with a data compression rate, resulting in generation of compressed data having a first data quality. The service decompresses the compressed data, resulting in generation of decompressed data. The service filters, from the decompressed data, data that is identified as belonging to a selected class of data. The service causes an ML classifier to perform a classification operation on the data that is identified as belonging to the selected class of data. The service determines a classification accuracy of the classification operation performed by the ML classifier. The service determines whether the classification accuracy at least meets a threshold accuracy requirement. If the threshold is met, the data compression rate is increased; otherwise, it is decreased.