International Business Machines Corporation
DYNAMIC AUGMENTATION BASED ON DATA SAMPLE HARDNESS

Abstract:

In an approach for dynamic augmentation based on data sample hardness for training a learning model, a processor defines one or more augmentations for a dataset for training the learning model. A processor applies the one or more augmentations to the dataset. A processor trains the learning model with the one or more augmentations. A processor measures hardness of one or more data samples in the dataset. A processor adjusts the one or more augmentations for the one or more data samples based on corresponding hardness of the one or more data samples. A processor applies the adjusted one or more augmentations to the dataset. A processor trains the learning model with the adjusted one or more augmentations applied to the dataset.