Reduction of the amount of training data by the neural network integrity constraint approach fostering green AI

Abstract The Neural Network Integrity Constraint (NNIC) approach is a novel technique that aims to improve the accuracy of neural network (NN) classifications by reducing misclassified instances using integrity constraints (ICs) derived from a held-out residual dataset (separate from the final test set). This ensures a leakage-free evaluation. The paper describes the NNIC approach and evaluates the effectiveness of the NNIC approach through six publicly available datasets. For each experiment, t