FIRST-TO-SATURATE SINGLE MODAL LATENT FEATURE ACTIVATION FOR EXPLANATION OF MACHINE LEARNING MODELS

A method is provided for a first to saturate single modal latent feature activation network. The method includes training, based on a plurality of training examples including a plurality of input features, a first machine learning model including a hidden node. The method includes determining a plurality of subsets of the plurality of input features including a minimum combination of the plurality of input features first to cause saturation of the hidden node. The method includes determining a hidden node ordered saturation list including a subset of the plurality of subsets. The method includes generating a sparsely trained machine learning model to determine an output for a training example of the plurality of training examples based on at least one input feature of the subset included in the hidden node ordered saturation list corresponding to the hidden node. Related methods and articles of manufacture are also disclosed.