Understanding the patterns that neural networks learn from chemical spectra

Abstract

We train a convolutional neural network to classify functional groups from infrared spectra. With explainability methods, we show the model uses the presence and absence of peaks, at fundamental and anharmonic frequencies for accurate classification.