VMware, Inc.
Augmenting Training Data Sets for ML Classifiers Using Classification Metadata

Abstract:

Techniques for augmenting training data sets for machine learning (ML) classifiers using classification metadata are provided. In one set of embodiments, a computer system can train a first ML classifier using a training data set, where the training data set comprises a plurality of data instances, where each data instance includes a set of features, and where the training results in a trained version of the first ML classifier. The computer system can further classify each data instance in the plurality of data instances using the trained version of the first ML classifier, the classifications generating classification metadata for each data instance, and augment the training data set with the classification metadata to create an augmented version of the training data set. The computer system can then train a second ML classifier using the augmented version of the training data set.