We present a comprehensive, stacking-based framework for combining deep learning with good old-fashioned machine learning, called Deep GOld. Our framework involves ensemble selection from 51 retrained pretrained deep networks as first-level models, and 10 machine-learning algorithms as second-level models. Enabled by today's state-of-the-art software tools and hardware platforms, Deep GOld delivers consistent improvement when tested on four image-classification datasets: Fashion MNIST, CIFAR10, CIFAR100, and Tiny ImageNet. Of 120 experiments, in all but 10 Deep GOld improved the original networks' performance.
@article{arxiv.2207.03757,
title = {Combining Deep Learning with Good Old-Fashioned Machine Learning},
author = {Moshe Sipper},
journal= {arXiv preprint arXiv:2207.03757},
year = {2022}
}